STATURE ESTIMATION AND SEX DETERMINATION: AN …

STATURE ESTIMATION AND SEX DETERMINATION: AN EVALUATION OF

THE RELIABILITY OF PHALANGE

By Keowali Phumkeson

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree Master of Science Program in Forensic Science

Graduate School, Silpakorn University Academic Year 2012

Copyright of Graduate School, Silpakorn University

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STATURE ESTIMATION AND SEX DETERMINATION: AN EVALUATION OF

THE RELIABILITY OF PHALANGE

By Keowali Phumkeson

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree Master of Science Program in Forensic Science

Graduate School, Silpakorn University Academic Year 2012

Copyright of Graduate School, Silpakorn University

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การประมาณความสงและระบเพศเพอประเมนหาความนาเชอถอจากการวดกระดกนวมอ

โดย นางสาวเกวล พมเกษร

วทยานพนธนเปนสวนหนงของการศกษาตามหลกสตรปรญญาวทยาศาสตรมหาบณฑต สาขาวชานตวทยาศาสตร

บณฑตวทยาลย มหาวทยาลยศลปากร ปการศกษา

ลขสทธของบณฑตวทยาลย มหาวทยาลยศลปากร

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The Graduate School, Silpakorn University has approved and accredited the Thesis title of

“Stature estimation and sex determination: An evaluation of the reliability of phalange” submitted by

Miss Keowali Phumkeson as a partial fulfillment of the requirements for the degree of Master of

Science in forensic science

............................................................................

(Assistant Professor Panjai Tantatsanawong,Ph.D.)

Dean of Graduate School

........../..................../..........

Thesis Advisor

1. Asst. Prof. Thongchai Taechowisan, Ph.D.

2. Asst. Prof. Thanaporn Rungruang, Ph.D.

Thesis Exanimation Committee

……………………………………….Chairman

(Pol. Lt. Col. Sarit Subpongsiri)

……………/………………./……………….

……………………………………….Expert

(Pol. Col. Kritsada Ribruemsarp)

……………/………………./……………….

……………………………………….Expert

(Asst. Prof. Thongchai Taechowisan, Ph.D.)

……………/………………./……………….

……………………………………….Expert

(Asst. Prof. Thanaporn Rungruang, Ph.D.)

……………/………………./……………….

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53312302 : MAJOR : FORENSIC SCIENCE

KEY WORD : PHALANGE/ANTROPOLOGY/PROXIMAL INTER-PHALANGEAL JOINT

KEOWALI PHUMKESON: STATURE ESTIMATION AND SEX

DETERMINATION : AN EVALUATION OF THE RELIABILITY OF PHALANGE.

THESIS ADVISORS : ASST.PROF.THONGCHAI TAECHOWISAN, Ph.D. 158 pp.

The objective of this study is to obtain whether forensic identification of the skeletal

structure of the hand bone is sufficient in determining the sex of the victim of a mass disaster or

criminal case. This study has analyzed the bones of 300 hands (150 males and 150 females, aged

between 20-60 years) from the staff of Bumrungrad International Hospital. It showsthe middle

finger on the right on both sexes is the most useful bone of stature estimation. Sexual

determination from phalange’s length shows higher prediction accuracy of sex determination than

from proximal inter-phalangeal joint wide at 75.7% and 62.3% respectively. The most useful of

sexual determination from proximal inter-phalangeal joint wide is the middle left in female = 58.0

% and from phalange’s length is thumb left in male = 79.2 %.The results show left finger is more

useful bone than the right one cause of less impact from regular activity. A suggestion in future

study is to collecting the hand bones from people in the same occupation and control the living

environment factor, the discriminant functions carried out by statistical analysis may aid the

forensic anthropologist when no other human skeletal remains suitable for identification are

available.

Department of Forensic Science Graduate School, Silpakorn University Student’s signature ………………………… Academic Year 2012

Thesis Advisor’s signature ………………………............

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53312302 : สาขาวชานตวทยาศาสตร

คาสาคญ: กระดกนวมอ/มนษยวทยา/กระดกขอตอนวขอบนสด

เกวล พมเกษร : การประมาณความสงและระบเพศเพอประเมนหาความนาเชอถอจากการวดกระดกนวมอ. อาจารยทปรกษาวทยานพนธ : ผศ.ดร. ธงชย เตโชวศาล. 158 หนา.

ในขนตอนการระบตวบคคลจากชนสวนรางกายมนษยทพบบอยในกรณภยพบตและความผดทางอาชญากรรมเปนสงสาคญทจะตองระบการประมาณความสงและระบเพศ ในการศกษานไดวจยกระดกนวมอ ตวอยางประชากรไทย(ชาย คน และ หญง คน ในชวงอายระหวาง - ป) จากพนกงานโรงพยาบาลบารงราษฎร อนเตอรเนชนแนล จากด (มหาชน) ผลการศกษาแสดงใหเหนวากระดกนวกลางดานซายของทงเพศหญงและชายเปนนวทมความสมพนธกบความสงของบคคลมากทสด การระบเพศจากความยาวของกระดกนวมอมความแมนยามากกวาจากความกวางของขอกระดกนวมอโดยมคาเทากบ . % และ . % ตามลาดบ นวทใหความแมนยาในการระบเพศจากความกวางของขอกระดกนวมอคอนวกลางดานซายในเพศหญง( . %)และ จากความยาวของกระดกนวมอคอนวหวแมมอดานซายในเพศชาย( . %) จากผลการศกษาแสดงใหเหนวากระดกนวมอดานซายมความแมนยามากกวาดานขวาเนองจากเปนมอขางทไมคอยถนดจงไมไดรบผลกระทบจากกจกรรมในชวตประจาวน และยงมขอเสนอแนะการเกบตวอยางจากกลมตวอยางในอาชพเดยวกนเพอเปนการควบคมปจจยภายนอกมอาจมผลตอการทดลอง โดยการวเคราะหทางสถตในการจาแนกนอาจชวยนกนตมานษยวทยาเมอกระดกมนษยสวนอนไมสามารถนามาใชในการระบตวบคคลได

สาขาวชานตวทยาศาสตร บณฑตวทยาลย มหาวทยาลยศลปากร ลายมอชอนกศกษา........................................ ปการศกษา 2554

ลายมอชออาจารยทปรกษาวทยานพนธ.....................................

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ACKNOWLEDGEMENT

This thesis could not successfully completed without the kindness of advisor’s team. First

and foremost to my major advisor, Asst.Prof.ThongchaiTaechowisan, who gave good advice and

be guidance of this thesis since start until successful. My co-advisor, Assoc.Prof.Dr.

ThanapornRungruang, who is a good guidance for experiment.Pol.Col. KritsadaRibruemsarp for

his appreciated suggestion. And the special thanks for Pol.Lt.Col. SaritSubpongsiri, for all of

comment and good suggestion including checked and corrected the fault of this thesis

I would like to special thank for Mr. Anuwat Panthoungthong and Ms. Waraphon

Kobkaew who is Manager, Medical Records department of Bumrungrad International Hospital

for their support during my graduation and thesis experiment.

Finally, My graduation would not be acheived without best wish from my parents,

Commander Kasem Phumkeson and Mrs.Sarinthip Phumkeson, who help me for everything and

always gives me greatest love, willpower and financial support until this study completed. And

the last gratefully special thanks to my relation and my friends for their help and encouragement.

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Table of Contents

Page

Abstract ..................................................................................................................................... d

Acknowledments ....................................................................................................................... f

List of Tables ........................................................................................................................... h

List of Figures ........................................................................................................................... j

Chapter

1 Introduction ................................................................................................................... 1

2 Review literature ........................................................................................................... 3

3 Materials and methods .................................................................................................. 29

4 Results ........................................................................................................................... 33

5 Discussion ..................................................................................................................... 56

Reference .................................................................................................................................. 60

Appendix ................................................................................................................................... 62

Biography .................................................................................................................................. 158

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List of Tables

Tables Page

1 Characteristic of pelvis on both sexes ................................................................. 16

2 TOD estimation based on kind of fabrics ........................................................... 23

3 Identification level of fractured bones ................................................................ 24

4 Frequency and percentage of sample by age ...................................................... 34

5 Descriptive statistics for stature and lengths of right and left phalanges in both

sexes ......................................................................................................... 34

6 Bilateral differences in measurements (cm) of phalanges in males and females

(Paired t – test) ......................................................................................... 36

7 Correlation coefficients between stature and lengths of each phalange on left

and right sides in both sexes .................................................................... 38

8 Mean and standard deviation of each proximal inter – phalangeal joint’s

Width in 5’s phalanges on both sexes ...................................................... 45

9 Difference’s comparison of each proximal inter – phalangeal joint’s

Width on both sexes (Paired t – test) ....................................................... 45

10 Sexual dimorphism comparison on both side of proximal inter – phalangeal joint’s

Width (Independent sample t – test) ........................................................ 46

11 Indications of each proximal inter – phalangeal joint’s Width are useful

Bones for sexual skeleton ........................................................................ 48

12 Accuracy of sexual predication from all proximal inter – phalangeal joint’s width

in total ...................................................................................................... 49

13 Mean and standard deviation’s phalange’ s length on both sexes ...................... 49

14 Difference’s comparison of each phalange’ s length on both sexes

(Paired t – test) ......................................................................................... 50

15 Sexual dimorphism comparison on both side of phalange’s length

(Independent sample t – test) ................................................................... 51

16 Indications of each phalange’s length on both sexes are useful bones for

sexual skeletons ....................................................................................... 53

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Tables Page

17 Accuracy of sexual predication from all phalange’s length on both sexes

in total ...................................................................................................... 54

18 The highest to lowest r value’s phalanges on both sexes .................................... 54

19 Linear regression equations for estimation of stature (cm) from lengths of each

phalange in female ................................................................................... 55

20 Discriminant sexual determinations proximal inter-phalangeal joint’s width

measurement ............................................................................................ 55

21 Discriminant sexual determinations from phalange’s length .............................. 57

22 Cut off values (in mm) and accuracy percentage for sex differentiation from

proximal inter - phalangeal joint’s width ................................................. 58

23 Cut off values (in mm) and accuracy percentage for sex differentiation from

phalange’s length ..................................................................................... 58

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List of Figures

Figures Page

1 W. H. Krogman ................................................................................................... 3

2 Remail from crime scene .................................................................................... 5

3 Instruments needed ............................................................................................. 6

4 Earl ...................................................................................................................... 13

5 Human skeleton .................................................................................................. 14

6 Author with “Earl” Kutztown University, PA .................................................... 15

7 Heavily damaged pelvis ...................................................................................... 16

8 Differences between the male and female pelvis ................................................ 17

9 Spreading caliper (left) and sliding caliper (right) .............................................. 17

10 Using a spreading caliper, taking a measurement from zy to zy ........................ 18

11 Using a sliding caliper, taking a measurement of nasal aperture ........................ 18

12 Age determination from tooth eruption .............................................................. 19

13 Endocranial suture closure date .......................................................................... 19

14 The age order of complete epiphyseal union ...................................................... 21

15 Long bones .......................................................................................................... 22

16 Anthroclub members Mandy, Jen and Allison ................................................... 25

17 Hand bones .......................................................................................................... 26

18 Measurement of each phalange’s length ............................................................. 31

19 Measurement of phalange;s length ..................................................................... 31

20 Measurement of each 1st metacarpal phalangeal joint’s width ........................... 32

21 Measurement of 1st metacarpal phalangeal joint’s width .................................... 32

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List of abbreviations

cm = centimeter

L1 = Thumb left

L2 = Index left

L3 = Middle left

L4 = Ring left

L5 = Little left

R1 = Thumb right

R2 = Index right

R3 = Middle right

R4 = Ring right

R5 = Little right

TOD = Time of death

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Chapter 1

INTRODUCTION

Background and Rationale

Many countries throughout the world have recently suffered from disaster and

conflagration. Identification of bodies is an important area of forensic science that helps to

repatriate victims back to their families. There are many techniques that can be used to identify

the body, even though in some cases, only some parts of the body are recovered.

This study aims to determine gender and estimate body structure through the

examination of the bones of the hand. Usually these factors are determined from examination of

the skull or pelvis; however it is not uncommon for these parts of the skeleton to be missing or

broken into fragments. In consideration of this, it will be of great benefit to forensic science if

gender can be determined from other parts of remains. In addition, identification by considering

bone structure is less time consuming, more financially economical, less complex and more

effective. Although, hand bone gender determination wouldn’t conclusively identify the victim it

will reduce the number of possible matches by 50% and estimate to nearest stature of victim only

but it would be useful in the order to give us a basic information to identify our victim which was

found at the crime scene.

Objectives

It’s to determine gender from phalanges and find correlation between

phalanges’s length and structure.

Hypothesis

Gender determination could be consider from hand bone and lengths of each

phalanges should have correlation with structure.

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Expected benefits and application Determination gender from hand bone would be benefit in forensic science and

estimation of structure bodies could be considering from the lengths of phalanges.

Limitation Determination gender and estimation structure of body could not be considered

under person who has metabolic bone disease such as osteoarthritis and arthritis.

Scope of Research This research is to determine gender and estimate approx. bodies’ structure by

analyzing from phalanges. We will measure length from distal, middle and proximal phalanges

including the circumference from inter-phalangeal joint and proximal inter-phalangeal joint which

will be recorded gender and stature from the staff of Bumrungrad International Hospital 300

cases. The person who has metabolic bone disease will be excluding from this research.

Definitions Phalanges is long bones of the fingers or toes, numbering 14 for each hand or foot:

two for the thumb or big toe, and three each for the other four digits

Anthropology is the study of human beings and their ancestors through time and

space and in relation to physical character, environmental and social relations, and culture

Proximal inter-phalangeal joint is joints between the phalanges of the fingers or toes, Stature is

the natural height of a human or animal in an upright position

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Chapter 2

REVIEW LITERATURE

History of Forensic Anthropology

Fig 1. W. M. Krogman who published “A Guide to the Identification of Human Skeletal

Material" in the FBI Law Enforcement Bulletin.

The forensic in physical anthropology’s knowledge has been started about 100 years

ago in the United States [1]. Later in year 1939; W.M. Krogman published "A Guide to the

Identification of Human Skeletal Material" in the FBI Law Enforcement Bulletin,which been the

second period of forensic anthropology development.

During the times of World War II and the Korean War, physical anthropologist has

been involved to identify the departed victims of the war. The standard information of skeletal

development and variation in American populations inspired significant and systematic data

gathering and analysis are also needed. These became an important point of contribution in

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forensic anthropology’s visibility within the world of physical anthropology, and in the forensic

community.

The Physical Anthropology Section of the American Academy of Forensic Sciences

was established in 1972. Since then, 14 members has been expanded to over 200 members and is

still quickly growing. In 1977, division members formed the American Board of Forensic

Anthropology (ABFA) to examine and certify forensic physical anthropologists at the

postdoctoral level.

Forensic anthropologists [2] apply standard scientific techniques todevelop the

physical anthropology in the order to identify human remains, and to assist in the detection of

crime. The physical anthropologist’s ability is to understand the forms and variations of the

human skeleton in individuals and population complements the forensic pathologist’s emphasis

on soft tissue. Therefore, the application of knowledge concerning human skeleton biology has

been basis of forensic anthropology as a profession. Although, this focus has expanded by some

specialists to include: forensic taphonomy, which is the interpretation of mostly outdoor death

scenes and postmortem (after death) processes, and forensic archaeology, the recovery of

scattered or buried remains.

The examination process of human remains by the forensic anthropologist includes

three tasks. One of those tasks is providing a biological profile (age, sex, stature, ancestry,

anomalies, pathology, individual features) of the victim. The second task would be recreating the

postmortem period based on the condition of the remains and the recovery environment. Lastly,

they would provide data regarding the death event, including evidence of trauma occurring during

the per mortem period (time of the death).

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Fig 2. Remain from crime scene including skull, pelvis, fever, tibia and hair.

Taphonomy

Forensic Anthropologists are often called upon to partake in or even direct body

recoveries in outdoor settings. Knowledge about the human physical form and function must be

combined with scientific knowledge concerning postmortem changes in order to understand the

condition of human remains. For example, in an outdoor scene, these changes can be

characterized as decomposition of a body, alterations, scattering by scavengers, freezing, and the

like. Postmortem changes must be distinguished from ante mortem (immediately before death)

conditions in order for the anthropologist to estimate the correct time of death and so on.

Archaeology

Archaeology is a method of vital tools for the forensic anthropologist handling

recoveries, mainly when remains have been buried or scattered. Usually archaeology would be

included: infrared photography, metal detectors, and ground-penetrating radar. Accurate methods

of excavating buried remains can be critical in the location and interpretation of trace evidence

linked with the bodies. Archaeological methods demand complete documentation of the history

for each artifact, so maintaining a record for each piece of evidence recovered at a scene is a

normal part of the excavation process.

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Processing at crime scene.

Forensic physical anthropologist regularly participates in searches by law

enforcement or medical examiner officials. They can also participate in the recovery of remains in

a mass fatality incident or human rights investigation. These searches may be focused on a certain

location or a broad area. They may be done in conjunction with search and rescue teams, cadaver

dogs (dogs trained to find the scent of a decomposing body), or divers.

Processing a scene containing buried remains requires a significant amount of effort

and experience, especially if the remains are decomposed or skeletal. First, the area to be

examined will be gridded in order to preserve the information and layout of the scene. Before any

work is started, the area must be photographed and documented. Any living plants or insects

directly associated with the body after death must be collected. The excavation process involves

using small instruments such as the trowel(a shovel-like digging tool) and brushes. These tools

prevent any damage to the deteriorating tissue of the decomposing bodies. Once certain body

parts are photographed, they are usually bagged in order to prevent loss of small bones,

fingernails, teeth, or any other evidence.

Fig 3. Instruments needed such as the trowel (a shovel-like digging tool) and brushes.

The Forensic Anthropologist have to study about the bones because of the bones

often survive the process of decay and provide the main evidence for the human form after death.

Also the application of the science of physical anthropology is a legal process. Moreover the

identification of skeletal is hardly decomposed which is unidentified human remains is important

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for both legal and humanitarian reasons. Forensic anthropologists always apply standard scientific

techniques to develop the physical anthropology for identify human remains, and to assist in the

detection of crime. Forensic anthropologists frequently work in conjunction with forensic

pathologists, odontologists, and homicide investigators to identify a decedent, discover evidence

of foul play, and/or the postmortem interval. In addition to assisting in locating and recovering

suspicious remains, forensic anthropologists work to suggest the age, sex, ancestry, stature, and

unique features of a decedent from the skeleton."

Forensic Anthropologist is varying as there are crimes, people and places. After the

attacks on September 11, 2001, Forensic Anthropologists were deployed to a base in Delaware to

begin the tedious process of identifying bone fragments and teeth. They may be called upon to

identify bones and bone fragments placed at universities and museums.

When skeletonized remains are discovered, one needs to establish first if the bones are human. If

so, the sex, race, age, stature, weight, and any pathology of the newly acquired skeleton must be

established in order to make an identification of the remains, determine manner and cause of

death and, if homicide, identify the murderer. It is the job of the Forensic Anthropologist to

pursue these matters, make a report and possibly testify in court.

In recent years, just as the investigation of a crime scene has become more complex and

sophisticated, so has the task of the forensic anthropologist. Forensic anthropologists assist edictal

and legal specialists to identify known or suspected human remains.

The science of forensic anthropology includes archeological excavation; examination

of hair, insects, plant materials and footprints; determination of elapsed time since death; facial

reproduction; photographic superimposition; detection of anatomical variants; and analysis of past

injury and medical treatment. However, in practice, forensic anthropologists primarily help to

identify a decedent based on the available evidence.

For example, when a skeleton found in a wooded area is brought to a morgue or an

anthropologist's laboratory for examination, the first step is to determine whether the remains are

human, animal, or inorganic material. If human, an anthropologist then attempts to estimate age at

death, racial affiliation, sex, and stature of the decedent.

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If the skeleton shows evidence of prolonged burial or is accompanied by coffin nails

or arrow index, it usually represents an historic or prehistoric burial rather than a recent death.

Construction crews frequently unearth such skeletons during road or housing excavations. After

combining all of the evidence, the anthropologist determines the skeleton's possible significance

to medical and legal authorities.

Although the primary task of anthropologists is to establish the identity of a

decedent, increasingly they provide expert opinion on the type and size of weapon(s) used and the

number of blows sustained by victims of violent crime. It should be noted, however, that forensic

pathologists or related experts in forensic medicine determine the cause or manner of death, not

the forensic anthropologist.

Most anthropologists have advanced degrees in anthropology and have examined

hundreds of remains. They are also thoroughly familiar with human anatomy and how it varies in

different populations. Some anthropologists may also have experience in police science or

medicine, as well as in serology, toxicology, firearms and tool marks identification, crime scene

investigation, handling of evidence, and photography. A limited number of anthropologists deal

with footprint analysis and species identification of carrion insects in relation to estimating time

elapsed since death.

Perhaps the anthropologist's most valuable skill is familiarity with subtle variations

in the human skeleton. Although most adult skeletons have the same number of bones (206), no

two skeletons are identical. Therefore, observations of patterns or unique skeletal traits frequently

lead to positive identifications. The most frequently used method for identification is to compare

before- and after-death dental photo images. If such photo images do not exist, or if they are

unavailable, then old skeletal injuries or anatomical skeletal variants revealed in other photo

images may provide the comparative evidence necessary to establish a positive identification.

Hypothetical Example

Suppose hunters find a partially clothed skeleton lying on the ground in a heavily

wooded area with much of its clothing torn and scattered by carnivores. Law enforcement officers

are called to the scene, as is the medical examiner or non-physician coroner. The scene is

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photographed in detail, and the skeleton is examined and photographed before being removed to

the city morgue.

At the morgue, the medical examiner examines the remains for evidence of trauma,

such as stab marks in the shirt, blunt trauma to the skull and mandible, and broken bones. Photo

images and photographs of the body show that no bullets or pellets having been noted. Also,

examination of the clothing reveals no wallet or other personal identification.

The medical examiner determines through measurement of the pubic area that the

remains are those of a middle-aged adult male. There is no evidence of facial or head hair to aid

in determining racial affiliation. From measurements taken at the scene, the examiner roughly

estimates the stature. Also, a forensic odontology is called in to take dental photo images.

Although the decedent has a number of large dental cavities, he shows no restorations or evidence

of having seen a dentist. At this index, the medical examiner requests assistance from a forensic

anthropologist, who conducts further study of the remains in the laboratory.

The forensic anthropologist's examination confirms the medical examiner's findings

that the individual is a middle-aged male. However, questions remain that the forensic

anthropologist must answer, such as:

What is the individual's racial affiliation?

What is the individual's age and stature?

How long has the individual been dead?

Is there any evidence of trauma or foul play at or near the time of death?

Are there any distinguishing skeletal traits that may aid in establishing the identity?

Is there any indication of post-mortem treatment or alteration of the remains?

Racial Affiliation

The question of racial affiliation is difficult to answer because, although racial

classification has some biological components, it is based primarily on social affiliation.

Nevertheless, some anatomical details, especially in the face, often suggest the individual's race.

In particular, white individuals have narrower faces with high noses and prominent chins. Black

individuals have wider nasal openings and sub nasal grooves. American Indians and Asians have

forward-projecting cheekbones and specialized dental features.

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Examination of this skeleton reveals traits consistent with white racial affiliation.

Further examination of the skull produces a few strands of straight blonde hair. Microscopic

examination shows the hair to be consistent with that of a white person.

Age and Stature

Usually, examination of the pubic bone, sacroiliac joint, amount of dental wear,

cranium, arthritic changes in the spine, and microscopic studies of bones and teeth narrows the

age estimate given by the anthropologist. After examining the skeleton, these indicators suggest

that the man was between 35 and 45 years of age at the time of death.

Estimation of stature can be narrowed by measuring one or more complete long

bones, preferably a femur or tibia. If stature estimates are based on incomplete long bones, less

confidence can be placed in them. This measurement of the maximum length of the bone can then

be plugged into a formula based on race and sex to produce an estimate. In this case the

individual's stature was estimated at 5'7'' to 5'9'' with a mean stature of 5'8.''

Time Interval since Death

Estimating the time interval since death can be extremely difficult. For the most part,

such an estimate is based on the amount and condition of soft tissue, such as muscle, skin, and

ligaments present, the preservation of the bones, extent of associated plant root growth, odor, and

any carnivore and insect activity. However, many other variables must also be considered,

including the temperature at the time of death, penetrating wounds, humidity/aridity, soil acidity,

and water retention. The longer the time since death, the more difficult it is to determine the time

interval since death. In this hypothetical example, the anthropologist determined that the

individual died 6 to 9 months previously, based largely on the condition of the soft tissue and the

amount of root growth in the individual's clothing.

Evidence of Trauma

After the dirt and forest debris were removed from the bones using water and a soft

brush, a number of faint cuts became visible in the left ribs and the mid-back. The number of

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discrete cuts in three ribs and in one vertebra suggest that this male was stabbed a minimum of

three times. No additional evidence of trauma.

Distinguishing Skeletal Traits

Further examination revealed that the male sustained a fracture above his right eye

and upper jaw bone at least several years before death. The individual also had a severely

deviated nasal septum and presented evidence of a severe chronic nasal infection. This

observation is noteworthy because if he sought medical help for the fractures or sinus condition,

photoimages may have been taken that would provide an excellent opportunity for positive

identification.

Post-Examination Procedures

After the forensic anthropologist completes the examination, the medical examiner

provides all information obtained from the skeleton to the law enforcement officials investigating

the case. The information is then entered in the National Crime Information Center (NCIC).

In this hypothetical case, after several months, a search failed to locate a missing person matching

this description. Therefore, the medical examiner and the detectives returned to the forensic

anthropologist to request that a facial reproduction be attempted.

Two approaches are available to an anthropologist in reconstructing facial

appearance during life. First, the anthropologist could work with a composite artist experienced in

rendering sketches based on information supplied by eyewitnesses. Or, the anthropologist could

call in a specialist in three-dimensional facial reproduction, a technique in which the head is

constructed in clay directly over the skull and mandible or over good casts of them. Because of

limited funds, and because an experienced composite artist is available on staff, the forensic

anthropologist and artist worked together to produce a drawing of the person represented by the

skeletal remains. This drawing was then made available to the public via the local media.

Shortly thereafter, two unrelated men who had seen the image on television came forward

because they thought that it might be a relative. Medical and dental records for both individuals

could not be located, but facial photographs taken within the last 2 years were available.

12

Using new techniques of photographic superimposition and comparison, the forensic

anthropologist excluded one of the individuals outright. However, frontal photo images of the

second individual taken 3 years before death showed the individual was treated for facial injuries

sustained in a motor vehicle accident. The configuration of the frontal sinuses on the photo

images matched exactly the photo images of the recovered skull, thereby positively identifying

the victim.

Value of Forensic Anthropology

A forensic anthropologist makes significant contributions to an investigation. The

greatest of these could well be the anthropologist's intensive training and experience in

distinguishing between human and nonhuman remains, determining age at death, racial affiliation,

sex, stature, elapsed time since death, skeletal trauma, post-mortem damage and alteration of the

skeleton, and establishing positive identification based on skeletal and dental evidence. Such

information can be obtained from complete bodies or those partially destroyed by burning, air

crashes, intentional mutilation and dismemberment, explosions, or other mass disasters. In fact, a

forensic anthropologist is now an integral member of most mass disaster teams.

Through their anthropological training, most forensic anthropologists have

knowledge of excavation techniques and mapping that are invaluable in recovering evidence.

Consequently, the forensic anthropologist should participate in the investigation of the crime

scene and, especially, in the recovery of human skeletal remains.

Conclusion

Many forensic anthropologists offer their services to law enforcement agencies,

coroners, and medical examiners. However, if a law enforcement agency does not have access to

a forensic anthropologist, experienced experts can be found in many of the larger universities, in

anthropology museums throughout the United States, and in some medical examiner's offices. It

should be noted, however, that not all physical anthropologists are qualified to practice forensic

anthropology. A list of board certified forensic anthropologists can be obtained from the

American Academy of Forensic Sciences. Forensic anthropologists have much to contribute to

13

law enforcement and would welcome the opportunity to assist in the successful resolution of an

investigation.

Inventory and Profile

The Forensic Anthropologist will make a complete inventory of the bones received.

A sample inventory is show on the Case Report page and is always part of the final report

prepared on the case. The inventory used for this research is based on a partial skeleton recently

acquired by Kutztown University. For the purpose of this research, I will refer to the skeleton as

"Earl."

Fig 4. Earl (The name of owner skeleton in case report of this literature).

14

Fig 5. Human skeleton (A typical adulthuman skeleton consists of 206 bones. Individuals may

have more or fewer bones than this owing to anatomical variations. The most common variations

include additional (i.e. supernumerary) cervical ribs or lumbar vertebra. Sesamoidbone number

can also vary between individuals. The figure of 206 bones is commonly repeated but must be

noted to have some peculiarities in its method of counting).

As part of the inventory, generalized, non-specific words such as "cranium" are not

general used; rather, the specific bone that is present is described in detail. If three bones of the

skull are present and in good condition, each of the bones will be identified and described as

having no anomalies or pathology. For example, if the left parietal, the occipital, and the right

mastoid process were all that remained of the skull in question, they would be listed

independently in the inventory. If the skull is complete, that would be stated.

15

Fig 6. Author with "Earl" Kutztown University, PA.

Sex and Race

After completing the inventory, determinations must be made regarding sex and race.

We can sometimes get into a rut because in order to determine sex, we need to know the race. But

in order to determine the race, we need to determine the sex. Direct observation of certain features

help in the preliminary determination, however in order to deal with any inherent problems that

may come up, a number of measurements are taken of the skull and pelvis. In direct observation,

a trained eye and touch can separate male from female using the supraorbital margin, mastoid

process and genial flare parts of the skull. However, most important in direct observation is the

pelvis.

16

Table 1. Characteristic of pelvis on both sexes.

Male Female

General size Large Small

Architecture Rugged Smooth

Supraorbital margin Rounded Sharp

Mastoid process Large Small

Occipital bone Muscle lines and protuberance marked Muscle lines not marked

Glabella Bony Flat

Genial Angle Squared Wide angle

Palate Larger, broader, tends to be U-shaped Small, tends to be a parabola

Occipital condyles Large Small

Fig 7. Heavily damaged pelvis.

17

.

Fig 8. Differences between the Male and Female pelvis.

Fig 9. Spreading caliper (left) and sliding caliper (right).

18

Fig 10. Using a spreading caliper, taking a measurement from zy to zy.

Fig 11. Using a sliding caliper, taking a measurement of nasal aperture.

Age

The best bet in determining the age of a sub-adult skeleton is examination of the

teeth and jaw, when present. However, a comparative analysis may be made using the skull

sutures and epiphyseal fusion in the young-adult skeleton. Sutures are the zigzag "seams" where

the bones of the skull meet. Endocranial sutures (inside the skull) are more reliable as an aging

method than is ectocranial suture analysis. Epiphyseal fusion refers to the closing of the "growth

plates" at the ends of the long bones and clavicle, and iliac crest fusion. The teeth also become

important later in the identification of a specific individual.

19

Fig 13. Endocranial suture closure date.

Fig 12. Age determination from tooth.

20

Stature is determined using the another type of formula called "Regression Formula

for Estimating Maximum Living Stature (with standard errors) from Maximum Long Bone

Length" of the Humerus5. Optimally, the Forensic Anthropologist will have all 6 upper long

bones and all 6 lower long bones. Using the average of both right and left humeri, both right and

left ulnae and both right and left radii, along with the average of both right and left tibia, both

right and left fibulae and both right and left femurs, including the standard error, one can arrive at

a fairly accurate estimation of stature. This range is then used to estimate weight. An osteometric

board is used for obtaining precise measurements of the long bones. Weight is a function of the

stature determination. The end result will be a range of statures and weights based on the average

standard error.

Stature

3.26 x (humerus) + 62.10 = stature +/-4.43cm

3.42 x (radius) + 81.56 = stature +/-4.30

3.26 x (ulna) + 78.29 = stature +/-4.42

21

Fig 14. The age order of complete epiphyseal union (there will be 2 calculations for stature,

based on the upper and lower standard of error).

22

Weight

Wt (in lbs) = 4.4 x (stature in inches) - 143

(there will be 2 calculations for weight, based on the upper and lower standard of error)

Fig 15. Long bones (humerus, radius, ulna and hand) were articulated, so had to be folded back.

Estimating Time of Death

The first question to be asked and probably the most difficult to answer is "how long

has it been dead?" Bones do not decay as skin and soft tissue do, but they are subject to

weathering and scatter (taphonomy). Animal scattering of bones can destroy the context of the

crime scene and gnaw marks destroy actual bone. If a body is buried, insectscannot get at it, but

micro-organisms can. The acidity of soil will have an effect on bone.

Condition of bone depends on the type of burial or exposure along with temperature.

The "Body Farm" at the University of TN at Knoxville is a research facility dedicated to the

estimation of time of death. Bodies are in all stages of decay and students and faculty

meticulously record animal activity, smells, body temperatures, weather conditions. Early into the

decay process, a fair amount of skin and soft tissue remain and smells are at their worst. A partial

skeletalized body is one in which the bones are still articulated by cartilage and ligaments.

When a body is left on the surface, insect activity will begin immediately and within

2 weeks the body will be partially skeletalized, completely skeletalized within 8 months. If

buried, it will take between 1 and 2 years to become completely skeletalized and in arid areas may

become mummified.

23

Bone rot takes many years, and acidity in the soil speeds it up. Scatter is important to

the Forensic Anthropologist in estimating time of death/burial. The number and types of bones

available at the scene indicates the amount of time the body has been in that spot, i.e. smaller

bones get lost first.

TOD estimates based on environmental factors are from research in Tennessee as follows:

3 weeks -- articulated bones

5 weeks -- some scatter, some articulated

4 months -- disarticulated, within 10' circle

7 to 8 months -- most bones w/in 10' circle and all w/in 20'

1 year -- small bones missing, complete disarticulation

2 to 4 years -- some bones broken, scatterd 40', some large bones missing

12+ years -- bone rot; partial burial*

15 to 20 years -- no surface evidence

* partial burial from leaves, storms, erosion from shallow burial

Fabrics may aid the forensic scientist and/or detective in determining length of time since death.

Decay of fabrics is based on what the materials are and how long they've been there. Styles of

shoes and clothing also help pinindex dates. Below is a chart representing the most common types

of fabrics and exposure to various elements over time?

Table 2. TOD estimation based on kind of fabrics.

Material Length of Time in Good Condition (in months)

Rayon 1-2 if buried 5 on surface

Paper 1 in alk or fresh water 5 on surface/in acid*

Cotton/Wool 6 in alk or fresh water 10 to 15 on surface/in acid

Human Hair 10 to 15 if buried wind blows it away on surface

Cotton/Poly 15 on surface 25 to 35 if buried

Other Plastics/Leather 15 to 35 on surface >48 if buried

24

Manner and Cause of Death

Manner of death refers to the 5 possibilities: homicide, suicide, accidental, natural

and unknown. Cause of death refers to injury or disease, or combination that results in death and

could take months/years. Determining the cause of death is easier with a fleshed body and very

difficult with the flesh and organs gone.

Taking X-rays of the skeletal material is very important. One may note old damage

to bone that has healed, indicating that this injury did not directly lead to death. Damage from

metal objects leaves fragmented metal or metal shavings and saw tooth shavings will show up

bright white on X-ray. Bullets will leave fragments of lead.

Table 3. Identification level of fractured bones.

Type Characteristics

complete broken all the way through

incomplete crack; not all the way

comminuted piece not with the bone

linear pressure on skull, stress released by cracking; soft blunt weapon

stellate star-shaped piece missing; hard blunt weapon

depressed usually with stellate, piece pressed in; hard blunt object, sometimes sharp

weapon

broken hyoid if not adult, not fused; may indicate strangulation

timing linear cracks do not cross prior cracks; indicate order of attack

25

Fig 16. AnthroClub members Mandy, Jen and Allison.

Hand bones

The hand consists of 54 bones separated into three distinct regions, the wrist, the

palm, and the finger digits. The hand’s primary function is to allow the body to manipulate with

its environment, such as grasping and touching objects. Furthermore, the fingertips contain one of

the most densest regions of nerve endings in the human body [3].

Phalanges of hands

The phalanges of the hand are commonly known as the finger bones [4]. They are

fourteen in number, three for each finger, and two for the thumb.

Each consists of a body and two extremities.

The body tapers from above downward, is convex posteriorly, concave in front from

above downward, flat from side to side; its sides are marked by rough areas which give

attachment to the fibrous sheaths of the flexor tendons.

26

The proximal extremities of the bones of the first row present oval, concave articular

surfaces, broader from side to side than from front to back. The proximal extremity of each of the

bones of the second and third rows presents a double concavity separated by a median ridge.

The distal extremities are smaller than the proximal, and each ends in two condyles

(knuckles) separated by a shallow groove; the articular surface extends farther on the volar than

on the dorsal surface, a condition best marked in the bones of the first row.

The ungual phalanges, those most distal, are convex on their dorsal and flat on their

volar surfaces; they are recognized by their small size, and by a roughened, elevated surface of a

horseshoe form on the volar surface of the distal extremity of each which serves to support the

sensitive pulp of the finger.

Articulations.—In the four fingers the phalanges of the first row articulate with those

of the second row and with the metacarpals; the phalanges of the second row with those of the

first and third rows, and the ungual phalanges with those of the second row. In the thumb, which

has only two phalanges, the first phalanx articulates by its proximal extremity with the metacarpal

bone and by its distal with the ungual phalanx

Occasionally an additional bone, the oscentrale, is found on the back of the carpus,

lying between the navicular, lesser multangular, and capitate. During the second month of fetal

life it is represented by a small cartilaginous nodule, which usually fuses with the cartilaginous

navicular. Sometimes the styloid process of the third metacarpal is detached and forms an

additional ossicle.

In the ungual phalanges the centers for the bodies appear at the distal extremities of

the phalanges, instead of at the middle of the bodies, as in the other phalanges. Moreover, of all

the bones of the hand, the ungual phalanges are the first to ossify. The phalanges consist of three

sections. The proximal phalanges, the intermediate phalanges, and the distal phalanges.

Collectively, these bones make up the structure known as the fingers. (Diagram of the phalanges

is show at the top of the page).

27

Proximal Phalanges

The proximal phalanges are found at the base of the fingers, closest to the carpus.

These bones are longer than the carpal bones and play an important role in motion.

Intermediate Phalanges

The intermediate phalanges are found in between the proximal phalanges and distal

phalanges. There are four intermediate phalanges found on each hand, the only fingers that lacks

the intermediate phalanges are the thumbs. Like the distal phalanges, the intermediate phalanges

play an important role in motion and support of the hand.

Distal Phalanges

The distal phalanges are a series of bones found at the tip of the hand, following the

intermediate phalanges. The distal phalanges consist of five bones per hand and thus contribute a

total of ten bones to the human skeleton. These bones play an important role in movement and

functions of the hand.

Related research 1. “Sex determination using metacarpal biometric data from the Athens Collection”

by Sotiris K. Manolis a,*, Constantine Eliopoulos a, Christos G. Koilias b, Sherry C.

Foxaccessfrom Forensic Science International 193 (2009) 130.e1–130.e6. The sample collecting

993 metacarpals (left and right) from 151 adult individuals (84 males and 67 females) which is

the result indicated that metacarpals are useful bones for sexing skeletons of Greek origin with

highclassification accuracy (83–89%). The consequence of the differences in body size between

the two sexes. The statistical analysis conducted on the Athens Collection also indicates that

almost all male metacarpal measurements are significantly larger than those of females [3].

2. “Stature estimation from hand and phalanges lengths of Egyptians” by Sahar

Refaat Habib MD (Assistant Professor of Forensic Medicine & Toxicology) [4] , Nashwa Nabil

Kamal MD (Lecturer of Community Medicine) access from Journal of Forensic and Legal

Medicine 17 (2010) 156–160. A sample of 159 normal healthy Egyptian volunteers (77 females

28

and 82 males) was taken from students studying at ManiaUniversity, in the age bracket of 18–25

years. The result show that the regression equations were derived from hand and phalangelengths

and indicated that the stature can be estimated from them with SEE ranging from +4.54 to ±7.27

cm for both sexes.

29

Chapter 3

MATERIALS AND METHODS

The object of the research is aim to study about evaluation of the reliability of hand

bones. This is a descriptive and inferential statistic in order to determination gender and

estimation stature of victims by measure the length of phalange and width of proximal inter-

metacarpal phalangeal joint. Since we had reviewed the literature from Mania University as they

measured the length of phalange from the top of finger to the third of foldable joint but if we

review the anatomy theory carefully the phalange bone will appear all the way through

metacarpo-phalangeal joint isn’t the third of foldable joint instead. So this experiment we had

measured from the top of finger to metacarpo-phalangeal joint from alive people in the order to

record length of phalanges and for sexual determination,we had measured theproximal inter-

phalangeal joint’s width by using vernier caliper (Absolute Digimatic Caliper Series 500) Made

in Japan on both issue before analyze by SPSS

Materials

1. Phalanges

2. Vernier Caliper (Absolute Digimatic Caliper Series 500) Made in Japan

3. Gloves

4. Data record instrument

5. SPSS Program

30

Methods a. Indicate the problem

b. Assume hypothesis

c. Literature review

d. Research design

e. Prepare material

f. Measurement and analysis

g. Discussion and conclusion

h. Presentation

i. Research Design

Population and samples In this research, the study was directed at samples from staff of Bumrungrad

International Hospital because researcher working at this organization which sample group is

appreciates to co-operate with this research. Sampling by random from staff who under age

between 20-60 years 300 peoples.

Statistical analysis Using Statistical package for the social science following: The descriptive statistics

such as Percentage, Minimum, Maximum, Mean, Standard deviation, correalation and inferential

statistics such as linear regression analysis, Case wise

Methodology A. Estimation bodies’ structure

Independent Variable: Each sample’s length.

Dependent variable: Each phalange’s stature.

31

Fig 18. Measurement of each phalange’s length.

Fig 19. Measurement of phalanges’ length.

B. Determination gender from hand bond (proximal inter-phalangeal joint)

Independent Variable: Each 1stmetalparpal phalangeal joint wide.

Dependent variable: Sex.

32

Fig 20. Measurement of each 1st metacarpal phalangeal joint’s width.

Fig 21. Measurement of 1st metacarpal phalangeal joint’s width.

Collecting data

1. Record the gender and stature of each sample’s owner

2. Measure wide from proximal inter-phalangeal joint and phalanges’s length in millimeter

unit following:

3. Statistical analysis:One sample test, Paired t-test, Independent Samples t-test and

Discriminant.

4. Connectionism process by using spss

5. Blind test

33

Chapter 4

RESULTS

The result of stature estimation shows the length of middle left finger is the most useful

bone in the order to estimate stature which the mean on male show longer length than female. The

measurement in female show the middle, ring and little are statistically significant bilateral

difference and all male’s phalanges’s length and thumb, index in female aren’t statistically

significant bilateral difference. The correction of this study shows 80% by blind test. In the

meantime sexual determination indicated that phalange’s length is more useful bone than

proximal inter-phalangeal joint’s width in the order of sexual determination with classification

accuracy = 52.0%-79.2% and 50.7%-58.7%, respectively.

Determine sex from proximal inter-phalangeal joint width is 62.3% and the most useful

bone is thumb left in female and little left in male with 45% correction by blind test and from

phalange’s length is thumb left on both sexes with 60% correction by blind test.)

34

4.1. Estimation bodies’ structure

Table 4. Frequency and percentage of sample by age.

Age Male Female

Total % Total %

11-20 19 12.67 25 16.67

21-30 57 38.00 53 35.33

31-40 19 12.67 17 11.33

41-50 28 18.67 30 20.00

51-60 27 18.00 25 16.67

Total 150 100.00 150 100.00

Table 5. Descriptive statistics for stature and lengths of right and left phalanges in both sexes.

Statistic Female(n=300) Male(n=300) Min-Max Mean Std. Min-Max Mean Std.

H 143-183 158.55 5.97 154-189 173.03 6.08 L1 47.45-73.53 62.11 4.85 47.45-75.71 64.42 4.96 L2 72.63-99.47 87.46 5.33 72.54-106.89 90.11 5.78 L3 77.66-108.17 94.55 5.54 87.4-115.03 99.14 4.04 L4 52.01-101.66 87.86 6.56 73.02-109.78 90.75 6.09 L5 52.7-83.4 68.68 5.74 56.44-88.01 71.30 6.11 R1 47.45-90.45 62.61 5.16 51.44-76.98 64.95 4.52 R2 72.54-99.87 87.53 5.48 72.63-103.1 90.43 5.47 R3 79.05-108.33 95.21 5.52 85.71-116.25 99.36 4.42 R4 73.02-101.14 88.55 5.66 70.11-105.62 91.07 6.16 R5 54.64-89.72 70.55 6.17 13.60-87.73 70.94 7.61

As table 5the result shows the minimum – maximum, mean value and Std Deviation of

stature is following:

Stature:Female: Stature in between 143-183 cm, mean value 158.55 cm and Std

Deviation 5.97 cm

Male: Stature in between 154-189 cm, mean value173.03 cm and Std Deviation 6.08 cm

35

L1: Female: L1’s length in between 47.45-73.53 cm, mean value 62.11 cm and Std

Deviation 4.85 cm

Male: L1’s length in between 47.45-75.71 cm, mean value 64.42 cm and Std Deviation

4.96 cm

L2 :Female: L2’s length in between 72.63-99.47cm, mean value87.46cm and Std

Deviation 5.33cm

Male: L2’s length in between 72.54-106.89cm, mean value90.11cm and Std Deviation

5.78cm

L3: Female: L3’s length in between 77.66-108.17cm, mean value94.55cm and Std

Deviation 5.54cm

Male: L3’s length in between87.4-115.03cm, mean value99.14 cm and Std Deviation

4.04 cm

L4: Female: L4’s length in between 52.01-101.66cm, mean value87.86 cm and Std

Deviation 6.56cm

Male: L4’s length in between73.02-109.78cm, mean value90.75cm and Std Deviation

6.09cm

L5: Female: L5’s length in between 52.7-83.4cm, mean value68.68 cm and Std Deviation

5.74 cm

Male: L5’s length in between 56.44-88.01 cm, mean value71.30 cm and Std Deviation

6.11cm

R1: Female: R1’s length in between 47.45-90.45 cm, mean value62.61 cm and Std

Deviation 5.16 cm

Male: R1’s length in between 51.44-76.98cm, mean value64.95 cm and Std Deviation

4.52cm

R2: Female: R2’s length in between 72.54-99.87cm, mean value87.53 cm and Std

Deviation 5.48cm

Male: R2’s length in between72.63-103.1cm, mean value90.43cm and Std Deviation

5.47cm

36


Deviation 5.52 cm

Male: R3’s length in between 85.71-116.25 cm, mean value99.36 cm and Std Deviation

4.42cm


Deviation 5.66 cm

Male: R4’s length in between 70.11-105.62 cm, mean value91.07 cm and Std Deviation

6.16cm


Deviation 6.17 cm

Male: R5’s length in between 13.60-87.73cm, mean value70.94cm and Std Deviation

7.61cm

Table 6. Bilateral differences in measurements (mm) of phalanges on both sexes (Paired t- test).

Variable Female (n=300) Male (n=300) Std. t P-value Std. t P-value

Thumbs 4.74828 -1.292 .198 4.35566 -1.456 .147 Indexs 2.89117 -.321 .749 2.83331 -1.363 .175 Middles 3.20544 -2.543 .012* 2.34899 -1.301 .195 Rings 3.76897 -2.224 .028* 2.98365 -1.347 .180 Little 4.70483 -4.887 .000* 5.48195 .779 .437

* Significant at p < 0.05.

As table 6 the depict the bilateral differences (differences in the means) in measurements of

phalanges for both the sexes following.

Thumbs

Female: It is observed that there aren’t statistically significant bilateral difference (P-

value = 0.198>0.05)

Male: It is observed that there aren’t statistically significant bilateral difference (P-value

= 0.147>0.05)

37

Index

Female: It is observed that there aren’t statistically significant bilateral difference (P-

value = 0.749>0.05)


= 0.175>0.05)

Middle

Female: It is observed that there are statistically significant bilateral difference (P-value =

0.012<0.05)


= 0.195>0.05)

Ring


0.028<0.05)


= 0.180>0.05)

Little


0.000<0.05)


= 0.437>0.05)

38

Table 7. Correlation coefficients between stature and lengths of each phalanx on both sexes.

Variable Value of r

Female Male

L1 0.406 0.074

L2 0.493 0.091

L3 0.571 0.136

L4 0.478 0.013

L5 0.415 0.055

R1 0.395 0.006

R2 0.506 0.089

R3 0.538 0.114

R4 0.526 0.03

R5 0.253 .023*


As table 7the illustrates the correlation coefficients between stature and lengths of each phalange

on left and right sides in both sexes following.

Regarding to the phalanges’s lengths, it is observed that the left middle phalange on

both sexes (L3) gives the highest correlation with stature(r = 0.571and 0.136), respectively.

The second rank in correlation of stature in female and male show as right middle

phalange (r= 0.538 and 0.014), respectively

The regression analysis of stature estimation formulas from each phalange’s length is

linearity of relationships with stature, are significant at 0.05 and the regression formulas for

determine the stature from length of phalanges in both sex would be compute from = a+(bx)±c;

where “a” is the regression coefficient of the independent variable (constant) method), “b” is the

regression coefficient of each sample phalange’s length and “c” is the Std. Error of the Estimate.

All variable above (a,b,c) computed from linear regression in spss method. [7, 10]

39

Female

L1; Regression analysis of stature estimation formulas from L1 phalange’s length is

linearity of relationships with stature, significant at 0.05 and the regression formulas for

determine the stature from length of L1’sphalanges female and Std. Error of the Estimation would

be compute by:

S = 127.478 + (.500*L1)±5.47

Regarding to the analysis above, we have found the Std. Error of the Estimate = 5.47

cm and R2 =0.165or 16.5% which means independent variable (L1’s length of female) in this

regression formulas has an effect on dependent variable(stature) 16.5% and the rest of 83.5 %

came from other variable, instead.

L2; Regression analysis of stature estimation formulas from L2 phalange’s length is linearity of

relationships with stature, significant at 0.05 and the regression formulas for determine the stature

from length of L2’sphalanges female and Std. Error of the Estimation would be compute by:

S = 110.249 + (.552*L2)±5.20


cm and R2 = 0.243 or 24.3% which means independent variable (L2’s length of female) in this





from length of L3’sphalanges female and Std. Error of the Estimation would be compute by:

S = 100.379 + (.615*L3)±4.92


cm and R2 = 0.321 or 32.1% which means independent variable (L3’s length of female) in this





40

determine the stature from length of L4’sphalanges female and Std. Error of the Estimation would

be compute by

S = 120.343 + (.435*L4)±5.26

Regarding to the analysis above, we have found the Std. Error of the Estimate =

5.26cm and R2 = 0.228 or 22.8% which means independent variable (L4’s length of female) in

this regression formulas has an effect on dependent variable(stature) 22.8% and the rest of 77.2 %




from length of L5’sphalanges female and Std. Error of the Estimation would be compute by

S = 128.950 + (.431*L5)±5.45


5.45cm and R2 = 0.172or 17.2% which means independent variable (L5’s length of female) in this



R1; Regression analysis of stature estimation formulas from R1 phalange’s length is linearity of


from length of R1’sphalanges female and Std. Error of the Estimation would be compute by

S = 129.909 + (.458*R1)±5.50


cm and R2 = 0.156or 15.6% which means independent variable (R1’s length of female) in this






S = 110.321+ (.551*R2) ±5.17



41






S = 103.147 + (.582*R3)±5.05








S = 109.442 + (.555*R4)±5.09








S = 141.288 + (.245*R5)±5.79





42

Male



determine the stature from length of L1’sphalanges male and Std. Error of the Estimation would

be compute by:

S = 167.195+ (.091*L1)±6.09


cm and R2 =0.005or 0.5% which means independent variable (L1’s length of male) in this






be compute by:

S = 164.399+ (.096*L2)±6.08


cm and R2 = 0.008or 0.8% which means independent variable (L2’s length of male) in this





from length of L3’sphalanges male and Std. Error of the Estimation would be compute by:

S = 152.672+ (.205*L3)±6.05







43


be compute by

S = 174.223+ (-.013*L4)±6.10


6.10cm and R2 = 0.000or 0.00% which means independent variable (L4’s length of male) in this

regression formulas has an effect on dependent variable(stature) 0.00% and 100.0 % came from

other variable all.




be compute by

S = 169.110+ (.055*L5) ±6.09





R1; Regression analysis of stature estimation formulas from R1 phalange’s length is


determine the stature from length of R1’sphalanges male and Std. Error of the Estimation would

be compute by

S = 172.473+ (.009*R1) ±6.10


6.10cm and R2 = 0.000 or 0.0% which means independent variable (R1’s length of male) in this

regression formulas has an effect on dependent variable(stature) 0.0% and the rest of 100 % came

from other variable all.




be compute by

44

S = 164.115+ (.099*R2) ±6.08


6.08cm and R2 = 0.008or 0.8% which means independent variable (R2’s length of male) in this






be compute by

S = 157.342+ (.158*R3)±6.06


6.06cm and R2 = 0.013or 1.3% which means independent variable (R3’s length of male) in this






be compute by

S = 157.342+ (-.030*R4)±6.09


cm and R2 = 0.001or 0.1% which means independent variable (R4’s length of male) in this






S = 171.704+ (.019*R5)±6.10


cm and R2 = 0.001or 0.1% which means independent variable (R5’s length of male) in this

45



4.2 Sexual determination from proximal inter-phalangeal joint’s width.

Table 8. Mean and Std Deviation of each proximal inter-phalangeal joint’s width on both sexes.

Female Male Mean Std. Mean Std.

L1 18.8234 1.95583 19.2302 2.03458 L2 17.5127 1.51726 17.8250 1.78791 L3 17.6145 1.45912 18.0599 1.71369 L4 16.5479 1.39633 16.9095 1.62957 L5 14.4278 1.27863 14.9664 1.19927 R1 19.1091 1.78263 19.3773 2.17182 R2 17.8202 1.51374 17.9884 1.80885 R3 17.9700 1.47822 18.2849 1.83855 R4 16.8129 1.40519 17.1355 1.76920 R5 14.7391 1.39727 15.0943 1.26905


As table8 the result shows that the mean and Std. Deviation of each proximal inter-phalangeal

joint’s width in on male are generally wider than female. Beside, on the right hand are generally

wider than left hand on both sexes also.

Table 9. Bilateral differences in measurements (cm) of proximal inter-phalangeal joint’s widthon

both sexes (Paired t- test).

Female (n=300) Male (n=300) t P- t P-value

Thumb - .003* -1.699 .091 Index - .000* -2.142 .034* Middle - .000* -2.773 .006* Ring - .000* -2.953 .004* Little - .000* -2.103 .037*


46

Table 10. Sexual dimorphism comparison on both side of proximal inter-phalangeal joint’s width

(Independent sample t-test).

L= Left Independent sample t-test R= Right t P-value

Thumb L -1.768 .078 R -1.215 .024

Index L -1.621 .106 R -.936 .350

Middle L -2.409 .017* R -1.665 .097

Ring L -2.409 .017* R -1.665 .097

Little L -3.729 .000* R -2.345 .020*


As table 9, 10 at 95% confidence limits after paired t-test of both side of proximal inter-

phalangeal joint’s width on both sexes the result shows:

Female: It is observed that there are statistically significant bilateral difference (P-

value = 0.003, 0.000, 0.000, 0.000, 0.000<0.05) in thumbs, Index Middle, Ring and Little

respectively.

Male: It is observed that there mostly aren’t statistically significant bilateral

difference in indexs, middle, ring and little (P-value = 0.034, 0.006, 0.004 and 0.037<0.05),

respectively except thumb’s phalanges only (P-value = 0.091>0.05).

Thumbs

Left: P- Value = 0.078>0.05 which means aren’t statistically significant on sexual

dimorphism comparison.

Right- Value = 0.024<0.05 which means are statistically significant on sexual


47

Index

Left: P- Value = 0.106>0.05 which means aren’t statistically significant on sexual


Right- Value = 0.350>0.05 which means aren’t statistically significant on sexual


Middle

Left: P- Value = 0.017<0.05 which means are statistically significant on sexual


Right:P- Value = 0.097>0.05 which means aren’t statistically significant on sexual


Ring



Right:P- Value = 0.097>0.05 which means aren’t statistically significant on sexual


Little



Right: P- Value = 0.020<0.05 which means are statistically significant on sexual


48

Table 11. Indications of each proximal inter-phalangeal joint’s width are useful bones for sexual

skeletons.

Proximal

inter-

phalangeal

Side

Gender

Predicted

Total

Confidence

limit

(%)

Total of

confidence

limits (%) Female Male

Thumbs

Left Female 84 66 150 56.0 54.35

Male 71 79 150 52.7

Right Female 88 62 150 58.7 54.7

Male 74 76 150 50.7

Index

Left Female 80 70 150 53.3 52.3

Male 73 77 150 51.3

Right Female 83 67 150 55.3 54.65

Male 69 81 150 54.0

Middle

Left Female 83 63 150 58.0 56

Male 69 81 150 54.0

Right Female 83 67 150 55.3 54.65

Male 69 81 150 54.0

Ring

Left Female 82 68 150 54.7 53.7

Male 71 79 150 52.7

Right Female 81 69 150 54.0 54.65

Male 67 83 150 55.3

Little

Left Female 86 64 150 57.3 57.3

Male 64 86 150 57.3

Right Female 82 68 150 54.7 54.7

Male 68 82 150 54.7

49

Table 12. Accuracy of sexual predication from all proximal inter-phalangeal joint’s width in

total.

Sex Predicted

Total 1 2

Original

Count 1 90 60 150

2 53 97 150

% 1 59.7 40.3 100.0

2 35.3 64.7 100.0

As table12 the classification results shows as62.3% of original grouped cases correctly classified

4.3 Sexual determination from Phalange’s length

Table 13. Mean and Std Deviation’s phalange’s length on both sexes.

Female Male Mean Std. Mean Std. Deviation

L1 62.1101 4.85163 64.4235 4.95630 L2 87.4559 5.33152 90.1099 5.78386 L3 94.5451 5.53570 99.1415 4.03577 L4 87.8580 6.55835 90.7459 6.08709 L5 68.6751 5.74333 71.3041 6.10807 R1 62.6071 5.15817 64.9470 4.52436 R2 87.5296 5.47939 90.4294 5.46892 R3 95.2107 5.52225 99.3863 4.39824 R4 88.5542 5.66079 91.0730 6.16285 R5 70.5467 6.16850 70.9357 7.61248

As table 13the result shows that the mean and Std. Deviation of each phalange’s length in on

male are generally wider than female. Beside, on the right hand are generally wider than left hand

on both sexes also.

50

Table 14. Bilateral differences in measurements (cm) of proximal inter-phalangeal joint’s

widthon both sexes (Paired t- test).

Female (n = 300) Male (n = 300)

t P-value t P-value

Thumb -1.279 .203 Thumb -1.699 .091 Index -.314 .754 Index -2.142 .034 Middle -2.527 .013* Middle -2.773 .006* Ring -2.230 .027 Ring -2.953 .004* Little -4.849 .000* Little -2.103 .037

As table 14 at 95% confidence limits after paired t-test of both side of phalange’s length on both

sexes the result shows as follows:

Female: It is observed that there 2 phalanges are statistically significant bilateral

difference(P-value = 0.013, 0.000<0.05) in middle and little but there also 3 phalanges aren’t

significant bilateral difference which is (P-value = 0.203, 0.754, 0.027>0.05)in thumb, index and

ring, respectively.

Male: It is observed that there 2 phalanges are statistically significant bilateral

difference(P-value = 0.006, 0.004<0.05) in middle and ring but there also 3 phalanges aren’t

significant bilateral difference which is (P-value = 0.091, 0.034, 0.037>0.05)in thumb, index and

little, respectively.

51

Table 15. Sexual dimorphism comparison on both side of phalange’s length (Independent sample

t-test)

L= Left Independent sample t-test R= Right t P-value

Thumb L -4.044 .000* R -4.170 .000*

Index L -4.096 .000* R -4.588 .000*

Middle L -8.196 .000* R -7.241 .000*

Ring L -3.941 .000* R -3.699 .000*

Little L -3.852 .000* R -.484 .629

As table 15 the result shows following:

Thumbs

Left: P- Value = 0.000>0.05 which means are statistically significant on sexual


Right- Value = 0.000>0.05 which means are statistically significant on sexual

dimorphism comparison

Index

Left: P- Value = 0.000>0.05 which means are statistically significant on sexual

dimorphism comparison

Right: 0.000>0.05 which means are statistically significant on sexual dimorphism

comparison.

52

Middle

Left: 0.000>0.05 which means are statistically significant on sexual dimorphism

comparison.

Right: 0.000>0.05 which means are statistically significant on sexual dimorphism

comparison.

Ring


comparison.

Right: 0.000>0.05 which means are statistically significantonsexual dimorphism

comparison.

Little


comparison.

Right: 0.629>0.05 which means aren’t statistically significant on sexual dimorphism

comparison.

53

Table 16. Indications of each phalange’s length on both sexes are useful bones for sexual

skeletons.

Phalange Side Gender Predicted

Total Confidence

limits (%)

Total of

confidence (%) Female Male

Thumbs Left Female 107 43 150 71.3 75.26

Male 31 119 150 79.2

Right Female 91 59 150 60.7 60.33 Male 60 90 150 60.0

Index Left Female 90 60 150 60.0 60.00

Male 60 90 150 60.0


Middle Left Female 85 65 150 56.7 58.33

Male 60 90 150 60.0


Ring Left Female 94 56 150 62.7 70.33

Male 33 117 150 78.0


Little Left Female 78 72 150 52.0 57.33

Male 56 94 150 62.7


54

Table 17. Accuracy of sexual predication from all phalange’s length on both sexes in total.

sex Predicted Group Total 1 2

Original Count 1 107 43 150

2 30 120 150

% 1 71.3 28.7 100 2 20 80 100

As table 16 the classification results shows as 75.7% of original grouped cases

correctly classified.

Table 18. Blind test result of estimation stature from phalanges’s length.

No Sex S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

1 F 150.00 157.86 158.43 158.18 159.43 158.62 156.07 157.14 159.36 161.60 158.80

2 F 160.00 157.76 157.75 159.24 160.29 159.90 157.81 156.24 158.77 160.31 159.07

3 M 178.00 172.83 172.89 172.66 173.07 172.96 173.03 172.80 172.79 154.64 173.11

4 M 165.00 173.06 173.20 172.91 173.04 173.12 173.08 172.93 172.70 154.56 173.10

5 M 179.00 173.06 172.94 172.69 173.07 173.02 173.07 173.25 172.93 154.62 173.01

6 F 148.00 153.76 150.81 148.99 152.11 153.28 153.99 150.58 151.02 150.46 154.67

7 M 178.00 171.98 172.41 172.98 173.27 172.21 172.95 172.34 171.92 155.13 172.74

8 M 177.00 172.28 173.04 172.97 173.14 172.54 172.98 172.29 172.95 154.90 172.91

9 F 160.00 157.37 158.70 157.27 160.28 159.57 158.58 159.51 160.66 157.94 158.29

10 F 148.00 153.76 150.58 150.96 152.49 152.50 153.98 150.81 149.15 149.97 155.12

55

Table 19. Blind test result of sexual determination from 1st metalcarpalphangeal joint’s width.

No Sex L1 L2 L3 L4 L5 R1 R2 R3 R4 R5 Correct

1 F M M M M M M M M M M 1

2 M M M M M M M M M M M 10







9 M F F F F F F F F F F 8

10 F F F F F F F F F F F 10

Correct 4 4 4 5 5 4 5 5 5 4

Table 20. Blind test result of sexual determination from phalange’s length.

No Sex L1 L2 L3 L4 L5 R1 R2 R3 R4 R5 Correct

1 F F M M M M M M M M M 6










Correct 8 8 7 3 6 7 6 8 6 5

56

Chapter 5

DISCUSSION

The statistics for stature and phalanges ’length on both the sexes. Mean value,

standard deviation, and standard error of mean of hand and phalanges lengths in males ‘cases are

higher than female’s cases by independent sample t-test and depicts the bilateral differences by

paired t-test in phalange’s length on both sexes shows that there are no statistically significant

bilateral difference except in the middle, ring and little fingers in females. The most useful bone

for this study is mostly from left side because the general people using the right hand for activity.

So the left hand bone is less impact than right hand. Moreover sexual determination from

proximal inter-phalangeal joint width is only 45% correction reason of our female sample is a

nurse but male sample is back officer service which they have a different activity. Nurse(s) who

always doing more tough activity than back office staff. The correlation coefficient between

stature and lengths of hands and phalanges on both sexes as table 21.

By discriminant function analysis, their results show that the phalange’s length are

better than the proximal inter-phalangeal joint’s width for ability of determine gender correctly.

They achieved 62.3 % accuracy by using phalange’s length and 75.7% by using proximal inter

phalangeal joint’s width. Sexual prediction is more reliable in case of Thai males than in

females.The cut off values (mm) and accuracy percentage for sexual determination from proximal

inter-phalangeal joint’s width and phalange’s length as table22 and table 23 below.

57

As per blind test of 10 samples above, the stature of victim could be estimate from

phalanges length of 8 samples and the most useful bone is L2,L3,L4,L5,R2 and R3 = 80%,70%

=R4 and 60% = L1,R5 respectively.

The result of sexual determination from blind test is also support to the result above

which the phalange’s length is more accuracy than proximal inter-phalangeal joint’s width.

Table 21. Linear regression equations for estimation of stature (cm) from lengths of each

phalange on both sexes.

Sex Phalange Regression R2

Female

L1 S = 127.478 + (.500*L1)±5.47 16.50%

L2 S = 110.249 + (.552*L2)±5.20 24.30%

L3 S = 100.379 + (.615*L3)±4.92 32.10%

L4 S = 120.343 + (.435*L4)±5.26 22.80%

L5 S = 128.950 + (.431*L5)±5.45 17.20%

R1 S = 129.909 + (.458*R1)±5.50 15.60%

R2 S = 110.321+ (.551*R2) ±5.17 25.60%

R3 S = 103.147 + (.582*R3)±5.05 29.00%

R4 S = 109.442 + (.555*R4)±5.09 27.70%

R5 S = 141.288 + (.245*R5)±5.79 6.40%

Male

L1 S = 167.195+ (..091*L1)±6.09 0.50%

L2 S = 164.399+ (.096*L2)±6.08 0.80%

L3 S = 152.672+ (.205*L3)±6.05 1.90%

L4 S = 174.223+ (-.013*L4)±6.10 0.00%

L5 S = 169.110+ (.055*L5)±6.09 0.30%

R1 S = 172.473+ (.009*R1)±6.10 0.00%

R2 S = 164.115+ (.099*R2) ±6.08 0.80%

R3 S = 157.342+ (.158*R3)±6.06 1.30%

R4 S = 157.342+ (-.030*R4)±6.09 0.10%

R5 S = 171.704+ (.019*R5)±6.10 0.10%

58

Table 22. Cut off values (in mm) and accuracy percentage for sex differentiation from proximal

inter-phalangeal joint’s width.

proximal inter-phalangeal joint Side Discriminant Values(mm.) Female Male

Thumbs Left Female<19.02≤Male 56.0 52.7 Right Female<19.24≤Male 58.7 50.7

Index Left Female<17.66≤Male 53.3 51.3 Right Female<17.90≤Male 55.3 54

Middle Left Female<17.83≤Male 58.0 54 Right Female<18.09≤Male 55.3 54

Ring Left Female<16.68≤Male 54.7 52.7 Right Female<17.82≤Male 54.0 55.3

Little Left Female<14.68≤Male 57.3 57.3 Right Female<14.88≤Male 54.7 54.7

Table 23. Cut off values (in mm) and accuracy percentage for sex differentiation from phalange’s

length.

proximal inter-phalangeal joint Side Discriminant Values(mm.) Female Male

Thumbs Left Female<63.26≤Male 71.3 79.2 Right Female<67.73≤Male 60.7 60

Index Left Female<88.65≤Male 60 60 Right Female<88.95≤Male 58.7 67.3

Middle Left Female<90.31≤Male 56.7 60 Right Female<97.20≤Male 57.3 62.7

Ring Left Female<89.05≤Male 62.7 78 Right Female<89.69≤Male 60 72.7

Little Left Female<72.23≤Male 52 62.7 Right Female<70.73≤Male 55.3 64.7

The living environment of sample such as biological origin of a population sample is

(genetic), a restrictive factor in the use various of lifestyle, activities, food and career could be

affected to phalanges’ s length directly. People who doing a tough sport such as basketball,

volleyball could have phalange’s length longer than the person who didn’t usually work out. For

59

the above reasons, linear discriminant function equations were developed on a modern Thai

population only

Future study could be included the other part of proximal inter-phalngeal joint’s

width and control the kind of lifestyle of sample such as working behavior, age, would be show

more accuracy of these test discriminant equations in Thai’s sex determination. In addition, the

results of the present work may be used for the determination of sex of skeletons from forensic

contexts.

60

REFERENCE

[1] Steven N. Byers. (2007). Introduction of Forensic Anthropology. Third edition: 2-16.

[2] Terrie Winson. (2004). The Forensic Anthropologist. Accessed Jan 24. Available from:

http://www.anthro4n6.net/forensics/.

[3] Sotiris K. M, Constantine E, Christos G. K and Sherry C. F. (2009). “Sex determination

using metacarpal biometric data from the Athens Collection.” Forensic Science

International 193: 130.e1–130.e6.

[4] Sahar R. H., Nashwa Nabil Kamal. (2010). “Stature estimation from hand and phalanges

lengths of Egyptians.” Journal of Forensic and Legal Medicine17: 156–160.

[5] Prateek R. and Nagesh K. R. (2008). “Estimation of stature from hand dimension of north

and south Indians.” Legal Medicine10: 185-189.

[6] Tanuj K and Kewal K. (2011). “Anthropometry of hand in sex determination of

dismembered remains - A review of literature.” Journal of Forensic and Legal

Medicine 18: 14-17.

[7] Diane L. France. Forensic Anthropology a brief review. Accessed Jan 30. Available

from:http://www.wadsworth.com/anthropology_d/special_features/forensics/forensic

s_index/index.html.

[8] Prateek R. and Nagesh K.R. (2008). “Estimation of stature from hand dimension of north

and south Indians.” Legal Medicine10: 185-189.

[9] Francesco I, Giancarlo D.V.and Carlo P.C.(1998). “Sex determination by discriminant

analysis of patella Measurements.” Forensic Science International 95: 39–45.

[10] พชตพล แมนวงศ. (2553) “การกาหนดเพศโดยการวเคราะหจาแนกเพอประเมนหาคาความ

นาเชอถอในการวดกระดกฝามอในประชากรไทย.” วทยานพนธปรญญามหาบณฑต

สาขาวชานตวทยาศาสตร บณฑตวทยาลย มหาวทยาลยศลปากร. [11] อทศ ศรวชย. (2553). “การคาดคะแนสวนสงจากความยาวกระดกหนาแขงและกระดกปลาย

แขนดานในของประชากรไทย.” วทยานพนธปรญญามหาบณฑต สาขาวชานต วทยาศาสตรบณฑตวทยาลย มหาวทยาลยศลปากร, .

61

APPENDIX

62

Stature and phalange’s length measurement in Female (n=150)

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

1 178 59.96 84.06 92.28 89.53 65.55 68.21 85.68 91.86 85.99 67.68

2 165 60.74 82.58 90.19 80.96 58.73 58.95 80.79 87.81 82.21 64.46

3 159 65.60 90.16 86.23 91.58 74.46 58.29 85.02 100.5 94.80 72.84

4 158 65.85 94.02 98.55 91.96 75.26 65.97 97.10 101.6 93.07 70.33

5 160 55.86 80.98 89.02 82.99 62.32 56.14 82.58 88.79 81.52 63.67

6 154 71.88 79.81 84.54 78.16 62.93 67.53 84.85 89.76 77.33 68.29

7 150 60.44 80.64 92.01 82.99 56.74 60.57 77.88 93.96 81.93 58.08

8 159 60.27 81.27 88.20 84.22 64.76 61.21 79.05 89.93 81.55 61.01

9 162 64.36 82.96 96.01 85.84 67.73 59.00 86.37 93.09 87.48 67.57

10 164 73.53 91.89 101.6 90.27 70.73 70.72 91.00 101.9 98.09 75.94

11 150 60.77 87.29 93.99 89.85 68.85 57.11 84.97 96.59 93.97 71.46

12 160 63.04 87.91 96.65 90.22 74.07 65.79 90.22 96.84 91.42 73.73

13 160 59.85 85.62 97.47 89.45 71.87 69.58 91.37 97.3 90.48 73.08

14 165 61.61 86.57 96.72 86.13 59.36 67.18 89.33 99.50 93.68 66.81

15 150 51.19 77.60 86.85 84.23 61.56 54.91 84.45 94.08 84.86 64.95

16 159 61.02 89.77 99.71 90.08 65.96 64.78 93.8 101.1 95.03 73.78

17 155 68.66 88.44 92.69 88.97 68.40 65.07 79.29 90.83 86.06 70.35

18 160 61.20 89.29 95.03 91.95 72.62 61.15 87.08 99.21 94.92 77.79

19 163 64.82 94.75 103.7 96.40 75.48 67.37 96.13 105.3 98.05 76.68

20 156 64.54 85.96 88.33 81.99 62.48 63.83 88.42 92.88 85.53 68.70

21 155 59.82 79.33 83.19 52.01 52.70 59.73 80.90 83.97 77.93 59.30

22 163 63.26 85.92 93.54 91.02 67.17 60.22 84.66 94.34 85.34 68.77

23 156 60.32 84.62 93.89 85.52 61.31 65.74 84.68 96.66 90.75 68.43

24 165 58.39 94.68 95.08 82.75 69.27 61.04 89.51 100.40 90.55 70.93

25 161 59.50 83.46 97.73 90.09 70.94 90.45 81.40 94.60 89.67 70.65

26 160 60.57 86.05 95.71 91.83 71.82 60.92 83.34 95.58 91.65 72.56

63

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

27 167 69.06 91.68 99.55 90.65 72.02 65.22 93.76 98.77 93.97 79.17

28 157 59.79 80.41 94.69 83.69 63.04 59.14 82.11 93.16 86.16 68.30

29 157 64.59 93.32 100.2 94.96 73.19 62.63 93.04 102.68 95.97 79.68

30 158 57.14 83.80 88.32 81.91 67.77 55.20 84.86 93.59 86.23 67.10

31 154 54.69 89.05 93.44 87.01 67.63 59.38 89.80 99.49 90.76 66.25

32 162 62.42 89.42 98.34 88.33 71.77 60.44 90.72 95.06 90.05 74.88

33 161 62.82 91.18 96.81 92.15 67.28 60.47 90.96 99.52 93.55 71.93

34 155 60.33 81.69 92.43 84.31 62.40 64.02 82.78 96.01 91.23 67.57

35 173 68.16 95.16 104.8 92.69 68.85 68.59 95.72 102.30 92.44 74.89

36 149 60.49 80.89 88.07 83.51 66.13 60.12 78.42 87.64 85.72 67.09

37 147 60.81 84.41 86.63 79.33 61.76 66.55 80.42 85.15 77.51 68.28

38 155 61.54 85.51 90.25 85.56 69.34 63.73 87.98 93.65 85.49 68.81

39 164 62.38 92.98 101.3 93.98 76.15 65.54 92.99 105.88 98.22 81.63

40 150 57.01 84.24 89.26 80.21 64.83 66.16 87.63 90.77 84.37 71.02

41 160 61.15 85.99 95.16 88.18 69.78 57.92 87.93 95.57 88.44 72.47

42 165 70.91 95.46 101.7 98.65 79.03 64.01 90.44 101.18 98.07 80.33

43 153 57.59 81.66 88.42 82.53 63.93 56.98 80.98 95.28 86.56 68.37

44 150 59.77 92.6 102.1 97.29 76.26 60.77 91.99 102.13 97.85 77.32

45 160 61.02 88.31 95.19 91.64 71.79 63.11 93.51 101.93 91.57 73.18

46 152 68.30 93.69 99.22 93.74 72.32 63.71 94.00 100.33 93.76 76.60

47 165 64.41 95.16 101.9 95.55 75.05 66.21 94.11 97.75 96.04 76.83

48 155 60.13 85.65 93.27 81.42 66.10 58.29 89.55 94.10 85.29 65.82

49 163 57.29 87.16 94.54 84.33 61.48 59.78 89.87 96.30 86.75 61.76

50 155 66.51 85.46 94.71 91.87 74.05 68.46 88.35 96.43 92.18 76.52

51 145 53.08 80.38 86.07 84.2 65.46 59.51 81.10 90.37 84.83 69.22

52 160 59.92 92.82 98.28 90.03 70.58 63.15 85.60 98.75 91.91 69.93

53 157 65.89 86.23 92.12 86.67 66.98 64.18 90.85 99.32 91.31 75.05

64

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

54

55

162

150

60.85

57.97

81.37

89.31

90.64

93.21

81.71

82.59

66.28

66.04

56.62

60.64

82.33

86.98

87.05

91.32

83.85

84.88

70.74

70.69

56 152 58.57 83.74 91.64 86.45 64.79 60.44 87.18 89.90 82.35 78.83

57 155 58.42 87.23 92.20 80.60 60.93 62.45 86.89 92.43 85.66 70.98

58 157 61.23 87.23 91.72 86.17 69.30 70.04 91.31 93.34 84.49 70.31

59 155 62.21 91.77 95.82 88.11 65.86 60.81 88.66 96.73 88.32 72.78

60 158 64.36 92.68 99.07 90.09 70.59 60.87 90.58 98.87 91.31 70.68

61 158 57.07 83.83 91.18 85.02 65.19 61.46 85.91 95.66 90.30 72.57

62 160 55.91 84.89 91.61 82.24 60.38 63.45 84.78 87.03 82.99 62.49

63 155 56.21 89.83 96.60 92.96 68.90 62.42 88.64 95.43 89.24 70.75

64 156 60.41 91.89 96.91 90.31 69.59 64.55 94.57 97.02 89.51 76.11

65 160 59.03 91.76 98.56 88.76 73.51 58.33 88.03 98.28 88.88 75.87

66 157 52.59 81.19 94.61 87.03 69.68 58.84 85.01 92.69 87.75 69.03

67 155 59.11 87.53 98.30 91.27 67.36 58.45 89.41 96.71 90.44 77.50

68 155 55.46 85.30 94.74 88.93 70.61 60.05 83.98 90.64 87.12 72.24

69 150 56.41 84.37 89.08 84.67 66.17 54.68 86.05 87.75 83.18 71.95

70 150 59.42 76.84 85.18 77.22 59.13 58.92 79.84 83.63 75.36 59.42

71 183 69.79 98.70 108.2 101.7 78.30 68.28 99.87 108.33 101.14 80.76

72 152 61.81 81.9 84.90 79.42 61.10 57.40 82.73 86.67 82.41 64.40

73 165 62.45 89.38 96.00 89.05 68.68 61.03 90.27 95.97 89.47 71.30

74 155 69.46 88.53 95.38 86.59 66.73 60.07 82.64 95.36 89.33 72.23

75 155 64.43 91.66 98.74 90.76 72.99 66.90 89.08 97.20 92.70 73.61

76 148 52.56 73.48 79.05 73.02 56.44 52.57 73.07 82.25 73.90 54.64

77 164 70.05 94.55 102.3 98.80 77.31 67.39 94.53 102.71 96.05 80.79

78 160 58.89 92.83 95.98 85.80 67.36 61.84 92.89 97.92 91.29 72.69

79 148 47.45 78.96 82.86 80.16 67.17 51.44 83.46 86.18 81.31 60.06

80 175 64.96 96.54 101.6 99.02 75.64 68.39 98.94 102.89 96.31 81.46

65

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

81 143 55.95 76.01 83.71 78.08 58.07 50.14 78.02 84.40 76.19 89.72

82 157 59.71 87.12 93.51 85.46 68.06 61.47 85.16 95.06 89.17 69.72

83 160 66.25 85.62 91.44 80.53 64.18 60.03 80.29 86.58 92.12 86.36

84 160 65.76 93.50 98.42 87.50 70.16 65.39 96.59 99.39 91.91 73.31

85 163 61.10 85.92 93.44 85.33 68.77 59.40 84.84 91.97 85.61 69.51

86 149 55.11 79.40 85.49 75.92 62.34 60.81 80.39 85.33 80.87 62.65

87 152 65.69 87.64 91.13 82.52 64.96 58.59 84.83 89.69 82.02 66.53

88 160 63.55 92.05 96.33 87.39 67.29 60.13 88.72 96.37 89.69 69.58

89 158 65.35 84.65 88.74 80.87 67.39 62.35 80.94 89.15 86.51 69.15

90 148 55.08 72.63 77.66 70.11 55.30 56.09 72.54 82.11 74.31 61.32

91 177 64.90 89.23 100.9 89.07 70.13 65.36 91.97 101.24 97.52 71.15

92 158 68.33 89.21 98.07 92.84 70.59 60.60 86.71 97.84 93.10 71.77

93 159 61.30 90.60 98.62 89.98 69.55 64.11 92.29 98.96 89.69 69.4

94 160 62.76 97.26 104.7 97.26 77.33 71.12 95.27 104.35 95.50 72.58

95 158 62.24 87.71 97.77 89.97 73.82 61.95 88.43 97.51 88.78 69.93

96 160 58.96 83.12 93.60 83.07 61.74 62.12 86.43 94.94 82.88 63.75

97 160 54.68 81.88 90.02 83.15 64.95 62.52 85.80 95.43 86.05 67.39

98 160 64.40 86.85 97.14 87.91 66.56 65.56 89.68 98.03 85.75 66.85

99 161 58.48 88.65 98.94 92.05 73.48 66.52 89.38 99.72 93.80 74.5

100 159 65.42 84.68 94.53 84.91 68.06 60.08 88.29 95.78 88.58 69.79

101 158 62.34 82.61 88.56 82.43 68.30 69.43 80.01 90.20 85.79 67.18

102 161 65.70 91.05 100.94 90.05 72.68 63.89 93.71 101.58 92.59 74.07

103 158 63.89 84.13 92.08 84.98 66.43 64.34 83.72 95.27 86.85 67.37

104 160 57.04 83.58 96.25 89.35 69.50 65.91 86.52 96.14 90.84 67.95

105 159 67.48 86.45 92.08 84.11 69.37 65.31 86.49 97.55 83.54 72.6

106 160 62.20 83.42 86.43 81.42 62.32 66.16 81.12 89.34 81.34 57.88

107 159 65.45 84.72 91.29 88.49 72.23 63.96 86.70 93.39 88.10 75.58

66

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

108 156 57.72 86.45 95.29 89.32 72.26 62.23 89.41 94.65 90.71 70.36

109 161 66.21 94.11 97.75 96.04 76.83 64.41 95.16 101.9 95.55 75.05

110 159 64.85 94.02 98.55 91.96 75.19 65.97 97.10 99.88 93.07 70.29

111 165 66.90 89.08 97.20 92.70 73.61 64.43 91.66 98.74 90.76 72.99

112 160 60.44 80.00 92.01 82.99 56.69 60.57 77.88 93.96 81.93 58.08

113 162 59.96 84.12 92.28 89.53 65.5 68.21 85.68 91.86 85.95 67.62

114 164 70.91 95.46 101.7 98.65 79.03 67.94 92.44 101.18 98.07 80.33

115 160 62.35 80.94 89.15 86.51 69.15 65.35 84.65 88.74 80.87 67.39

116 167 66.83 92.26 98.67 90.74 68.86 64.5 88.95 97.66 88.57 71.00

117 158 67.70 99.47 104.8 100.8 79.29 67.13 94.82 101.5 95.38 79.93

118 160 62.20 93.86 100.8 99.83 79.87 61.81 95.34 104.6 96.05 79.16

119 165 64.09 89.09 100.2 92.43 69.50 64.33 95.32 100.5 90.09 61.21

120 162 69.63 88.22 98.18 93.88 67.53 71.65 91.77 100 90.25 71.63

121 164 66.21 93.75 97.84 95.60 75.13 59.12 92.94 103.2 96.31 77.69

122 160 70.72 91.11 101.9 98.09 75.94 73.53 91.89 97.63 90.27 70.73

123 165 57.11 84.97 96.59 93.97 71.46 60.77 87.29 93.99 89.85 68.85

124 158 65.79 90.22 96.84 91.42 73.73 63.04 87.91 96.65 90.22 74.07

125 160 69.58 91.37 97.30 90.48 73.08 59.85 85.62 97.47 89.45 71.87

126 154 67.18 89.33 99.50 93.68 66.81 61.61 86.57 96.72 86.13 59.36

127 161 54.91 84.45 94.08 84.86 64.95 51.19 77.60 86.85 84.23 61.56

128 158 55.20 84.86 93.59 86.23 67.10 57.14 83.80 88.32 81.91 67.77

129 154 59.38 89.80 99.49 90.76 66.25 54.69 89.05 93.44 87.01 67.63

130 162 60.44 90.72 95.06 90.05 74.88 62.42 89.42 98.34 88.33 71.77

131 161 60.47 90.96 99.52 93.55 71.93 62.82 91.18 96.81 92.15 67.28

132 155 64.02 82.78 96.01 91.23 67.57 60.33 81.69 92.43 84.31 62.40

133 155 66.90 89.08 97.20 92.70 73.61 64.43 91.66 98.74 90.76 72.99

134 148 52.57 73.07 82.25 73.90 54.64 52.56 73.48 79.05 73.02 56.44

67

No S L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

135 164 67.39 94.53 101.05 96.05 80.79 70.05 94.55 101.2 98.80 77.31

136 160 61.84 92.89 101.92 91.29 72.69 58.89 92.83 95.98 85.80 67.36

137 148 51.44 83.46 86.18 81.31 60.06 47.45 78.96 82.86 80.16 67.17

138 158 68.21 85.68 91.86 85.99 67.68 59.96 84.06 92.28 89.53 65.55

139 165 58.95 80.79 87.81 82.21 64.46 60.74 82.58 90.19 80.96 58.73

140 158 65.97 94.10 98.62 93.07 70.33 65.85 94.02 98.55 93.96 72.26

141 160 56.14 82.58 88.79 81.52 63.67 55.86 80.98 89.02 82.99 62.32

142 154 67.53 84.85 89.76 77.33 68.29 71.88 79.81 84.54 78.16 62.93

143 159 65.60 90.16 86.23 91.58 74.46 58.29 85.02 100.5 94.80 72.84

144 160 59.79 87.78 92.50 91.82 71.04 62.59 89.28 98.82 87.39 69.39

145 160 67.31 94.78 95.34 94.36 71.35 64.19 93.39 95.94 92.63 71.35

146 158 72.41 93.43 95.00 90.01 83.44 73.03 92.87 94.57 89.98 88.01

147 155 66.48 92.33 101.2 88.55 66.97 70.41 89.89 99.89 88.04 70.93

148 167 66.83 92.26 98.67 90.74 68.86 64.5 88.95 97.66 88.57 71.00

149 158 67.70 94.43 99.77 95.01 79.29 67.13 94.82 98.52 95.38 79.93

150 162 62.20 93.86 99.83 97.45 79.87 61.81 95.34 97.43 96.05 79.16

Stature and phalange’s length measurement in Male (n=150)

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

1 167 66.83 92.26 98.67 90.74 68.86 64.50 88.95 97.66 88.57 71.00

2 158 67.70 99.47 104.75 100.77 79.29 67.13 94.82 101.52 95.38 79.93

3 172 62.20 93.86 100.75 99.83 79.87 61.81 95.34 104.62 96.05 79.16

4 176 64.09 89.09 100.16 92.43 69.50 64.33 95.32 100.53 90.09 61.21

5 170 69.63 88.22 98.18 93.88 67.53 71.65 91.77 100.03 90.25 71.63

6 164 66.21 93.75 101.84 95.60 75.13 59.12 92.94 103.22 96.31 77.69

7 172 55.91 86.13 98.89 94.19 72.64 58.14 87.25 100.73 94.11 74.73

68

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

8 170 61.89 91.25 101.64 96.78 75.37 76.63 92.97 102.81 92.51 76.52

9 175 69.99 89.89 98.01 87.91 72.30 76.98 93.27 102.60 93.90 71.27

10 178 58.29 85.02 100.52 94.80 72.84 65.60 90.16 101.44 91.58 74.46

11 170 62.59 89.28 98.82 87.39 69.39 59.79 87.78 92.50 91.82 71.04

12 170 64.19 93.39 102.68 92.63 71.35 67.31 94.78 102.75 94.36 71.35

13 180 73.03 103.36 115.03 109.78 88.01 72.41 103.10 116.25 102.13 83.44

14 177 70.41 89.89 99.89 88.04 70.93 66.48 92.33 101.23 88.55 66.97

15 174 65.10 89.78 100.53 91.98 70.13 61.05 92.74 98.80 97.35 71.37

16 179 73.20 89.75 98.96 88.76 72.41 68.41 91.78 101.57 96.05 75.21

17 176 69.24 94.33 100.30 94.40 70.91 70.39 94.02 97.49 90.96 72.96

18 170 53.36 81.26 90.23 85.89 67.41 66.44 80.89 89.89 79.33 64.46

19 166 63.83 90.97 101.50 92.31 64.70 63.80 90.98 97.47 87.13 13.60

20 185 67.39 97.63 105.30 99.78 76.47 65.23 99.37 106.54 99.54 76.87

21 160 62.14 90.01 98.92 90.64 71.50 72.38 95.29 104.23 95.51 75.07

22 165 62.82 91.90 98.79 92.79 79.83 70.17 91.04 101.48 94.05 75.66

23 166 69.86 92.62 102.83 97.71 79.91 67.58 96.16 108.44 102.04 83.20

24 180 64.78 90.75 104.92 94.74 72.82 66.57 94.05 109.80 100.26 77.48

25 168 61.13 88.24 98.69 95.97 71.80 65.24 94.37 103.65 97.54 75.31

26 158 70.87 90.52 101.31 91.81 72.43 64.91 95.00 99.55 93.19 74.31

27 169 68.38 92.98 103.39 95.58 74.40 67.92 97.51 100.48 91.46 72.38

28 170 71.29 100.28 104.52 96.33 74.57 69.99 96.92 101.05 94.31 76.59

29 178 72.31 104.01 107.86 97.10 77.71 73.68 97.37 103.91 98.42 80.42

30 161 70.98 106.89 109.30 101.03 80.65 72.89 101.90 111.38 103.21 87.73

31 163 67.56 91.67 100.57 96.89 71.65 66.54 93.04 101.34 92.20 75.15

32 165 67.36 87.39 92.82 87.36 79.56 65.63 87.93 97.36 87.25 72.75

33 165 62.24 88.91 97.65 93.04 74.28 62.18 90.21 97.14 92.69 70.72

34 175 69.19 92.81 99.92 95.56 77.20 71.87 96.16 101.78 94.80 74.32

69

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

35 159 66.15 91.22 97.76 89.69 72.95 67.17 92.40 98.96 93.44 74.37

36 160 67.93 93.14 100.88 92.32 73.71 65.09 92.06 99.93 95.54 77.75

37 161 67.77 92.91 100.05 96.69 76.15 65.26 96.09 103.15 95.26 76.54

38 172 64.27 97.67 101.96 99.76 77.97 65.24 94.70 105.64 101.81 78.58

39 165 59.77 92.60 102.05 97.29 76.26 60.77 91.99 102.13 97.85 77.32

40 165 63.78 96.10 102.73 97.45 76.17 67.48 97.42 105.96 99.41 76.18

41 175 68.00 97.94 112.54 104.65 78.12 71.67 101.86 113.68 105.62 81.11

42 174 63.23 98.53 101.81 97.83 75.65 61.08 94.32 104.84 98.81 77.22

43 189 75.71 103.63 110.38 100.26 76.46 67.17 102.96 113.50 98.82 77.48

44 167 60.26 82.63 91.48 78.72 61.77 68.99 81.73 93.84 87.86 64.11

45 165 62.28 87.06 97.05 91.89 68.53 66.30 91.73 100.49 96.74 74.11

46 178 62.76 97.57 100.62 97.26 77.33 71.12 98.09 101.71 95.50 72.58

47 180 62.24 96.04 101.83 92.03 73.82 61.95 94.55 100.79 91.88 69.93

48 160 58.96 83.12 93.60 83.07 61.74 62.12 86.43 94.94 82.88 63.75

49 175 53.74 83.44 95.02 83.15 64.95 62.52 85.80 95.43 86.05 65.39

50 178 64.40 86.85 97.14 87.91 66.56 65.56 89.68 98.03 85.75 66.85

51 172 58.48 88.65 98.94 92.05 73.48 66.52 89.38 99.72 93.80 74.50

52 179 65.42 84.68 99.53 84.91 68.06 60.08 88.29 98.91 88.58 69.79

53 177 62.37 82.61 88.56 82.43 68.30 69.43 80.01 90.20 85.79 67.18

54 175 65.69 91.05 100.45 92.05 72.68 63.89 93.71 101.37 92.59 74.07

55 178 63.89 86.14 97.08 84.98 66.43 64.34 87.72 99.28 86.85 67.37

56 180 67.04 90.37 101.25 89.35 69.50 65.91 92.52 99.85 90.84 67.95

57 179 66.20 86.45 94.08 84.11 69.37 65.31 86.49 96.55 83.54 70.73

58 170 62.20 83.42 96.43 85.42 62.32 66.16 81.12 99.34 84.39 57.88

59 179 65.45 84.72 99.51 88.49 72.23 63.96 86.70 99.39 88.10 75.58

60 178 57.72 86.45 99.29 89.32 72.26 62.23 89.41 98.65 90.71 70.36

61 176 66.21 97.75 101.24 96.04 76.83 64.41 95.16 101.86 95.55 75.05

70

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

62 178 64.85 94.02 98.55 91.96 75.19 65.97 97.10 99.88 93.07 70.29

63 179 66.90 89.08 97.20 92.70 73.61 64.43 91.66 98.74 90.76 72.99

64 160 60.44 80.00 95.01 82.99 56.69 60.57 82.36 96.96 81.93 58.08

65 175 59.96 84.12 96.28 89.53 65.50 68.21 85.68 97.86 85.95 67.62

66 175 70.91 95.46 101.73 98.65 79.03 67.94 92.44 101.18 98.07 80.33

67 174 62.35 80.94 93.11 86.51 69.15 65.35 84.65 94.07 80.87 67.39

68 175 65.23 99.37 103.71 98.14 76.87 67.39 97.63 101.10 99.78 76.47

69 173 72.38 96.29 99.23 95.51 75.07 62.14 97.00 98.92 93.13 71.50

70 177 70.17 95.22 99.48 94.05 75.66 62.82 94.73 98.79 92.79 79.83

71 177 67.58 96.16 103.44 99.04 83.20 69.86 92.62 102.83 97.71 79.91

72 175 66.57 94.05 103.81 95.26 77.48 64.78 90.75 104.92 94.74 72.82

73 170 65.24 88.27 100.33 97.54 75.31 61.13 88.24 98.69 95.97 71.80

74 170 64.91 95.00 99.55 93.19 74.31 70.87 90.52 98.65 91.81 72.43

75 172 67.92 97.51 100.48 91.46 72.38 68.38 92.98 101.21 95.58 74.40

76 172 69.99 96.92 101.05 94.31 76.59 71.16 99.26 102.28 96.33 74.57

77 181 73.68 97.37 104.63 98.42 74.42 72.31 98.04 103.86 97.10 77.71

78 178 72.89 87.33 101.59 91.44 87.73 70.98 86.89 100.91 92.05 80.65

79 177 66.54 93.04 101.34 92.20 75.15 67.56 91.67 100.57 96.89 71.65

80 178 68.39 98.94 103.77 96.31 81.46 64.96 96.54 102.33 99.02 75.64

81 169 50.14 78.02 87.40 76.19 59.72 55.95 76.01 85.71 78.08 58.07

82 175 61.47 85.16 99.11 89.17 69.72 59.71 87.12 97.51 85.46 68.06

83 178 60.03 86.58 96.84 92.12 86.36 66.25 85.62 91.44 84.31 64.18

84 180 65.39 96.59 101.39 91.91 73.31 65.76 95.50 101.42 97.50 70.16

85 170 59.40 84.84 91.97 85.61 69.51 61.10 85.92 93.44 85.33 68.77

86 178 60.81 85.39 95.33 87.80 62.65 55.11 89.13 96.49 85.92 62.34

87 175 58.59 84.83 92.69 82.02 66.53 65.69 87.64 91.13 82.52 64.96

88 179 60.13 88.72 96.37 89.69 69.58 63.55 92.05 96.33 87.39 67.29

71

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

89 174 62.35 88.94 99.15 86.51 69.15 65.35 84.65 98.74 86.87 67.39

90 171 56.09 72.54 92.11 74.31 61.32 55.08 72.63 97.66 70.11 55.30

91 175 65.36 91.88 101.24 97.52 71.15 64.90 89.23 100.93 95.07 70.13

92 173 60.60 86.71 97.84 93.10 71.77 68.33 89.21 98.07 92.84 70.59

93 182 64.11 98.96 103.11 89.69 69.40 61.30 97.19 102.88 89.98 69.55

94 170 71.12 95.27 102.35 95.50 72.58 62.76 97.26 101.73 97.26 77.33

95 178 61.95 88.43 97.51 88.78 69.93 62.24 87.71 97.77 89.97 73.82

96 176 62.12 86.43 94.94 82.88 63.75 58.96 83.12 93.60 83.07 61.74

97 171 62.52 85.80 98.43 86.05 67.39 61.68 81.88 97.02 83.15 64.95

98 177 65.56 89.68 98.03 85.75 66.85 64.40 86.85 97.14 87.91 66.56

99 178 66.52 89.38 99.72 93.80 74.51 58.48 88.65 98.94 92.05 73.48

100 173 60.08 88.29 95.78 88.58 69.79 65.42 84.68 94.53 84.91 68.06

101 172 69.43 88.01 99.20 85.79 67.18 62.34 88.61 99.56 82.43 68.30

102 174 63.89 95.71 101.58 92.59 74.07 65.70 95.05 100.94 93.05 72.68

103 175 64.34 83.72 98.27 86.85 67.37 63.89 84.13 97.08 85.98 66.43

104 177 65.91 86.52 96.14 90.84 67.95 57.04 83.58 96.25 89.35 69.50

105 178 65.31 86.49 97.55 83.54 72.60 67.48 86.45 97.08 84.11 69.37

106 173 66.16 81.12 99.34 81.34 57.88 62.20 83.42 96.43 81.42 62.32

107 175 63.96 86.70 97.39 88.10 75.58 65.45 84.72 98.29 88.49 72.23

108 172 62.23 89.41 97.65 90.71 70.36 57.72 86.45 95.29 89.32 72.26

109 174 64.41 95.16 101.86 95.55 75.05 66.21 94.11 99.75 96.04 76.83

110 170 65.97 97.10 99.88 93.07 70.29 64.85 96.02 98.55 91.96 75.19

111 165 64.43 91.66 98.74 90.76 72.99 66.90 89.08 97.20 92.70 73.61

112 158 60.57 77.88 93.96 81.93 58.08 60.44 80.00 92.01 82.99 56.69

113 160 68.21 85.68 91.86 85.95 67.62 59.96 84.12 92.28 89.53 65.50

114 154 67.94 92.44 101.18 98.07 80.33 70.91 95.46 101.73 98.65 79.03

115 174 65.35 84.65 98.74 82.87 67.39 62.35 85.94 99.15 86.51 69.15

72

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

116 178 64.53 88.95 97.66 88.57 71.00 66.83 92.26 98.67 90.74 68.86

117 184 67.13 97.82 103.52 97.38 79.93 67.70 99.47 104.75 99.77 79.29

118 172 61.81 95.34 101.62 96.05 69.16 62.20 93.86 100.75 99.83 69.87

119 171 64.33 95.32 100.33 90.09 61.21 64.09 89.09 100.61 92.43 69.50

120 175 68.65 91.77 100.03 90.25 71.63 69.63 88.22 98.18 93.88 67.33

121 170 59.12 92.94 101.22 96.31 77.69 66.21 93.75 97.84 95.60 75.13

122 180 73.53 91.89 101.63 97.27 70.73 70.72 91.11 101.86 98.09 75.94

123 174 60.77 87.29 96.99 89.85 68.85 57.11 84.97 96.59 83.97 61.46

124 175 63.04 87.91 96.65 90.22 74.07 65.79 90.22 96.84 91.42 73.73

125 178 59.85 85.62 97.47 89.45 71.87 69.58 91.37 97.30 90.48 73.08

126 178 61.61 86.57 96.72 86.13 59.36 67.18 89.33 99.50 93.68 66.81

127 174 51.19 77.60 96.85 84.23 61.56 54.91 84.45 94.08 84.86 64.95

128 178 67.14 88.32 98.32 81.91 67.77 65.20 84.86 93.59 86.23 67.10

129 170 54.69 89.05 97.44 87.01 67.63 59.38 89.80 99.49 90.76 66.25

130 174 62.42 89.42 98.34 88.33 71.77 60.44 90.72 95.06 90.05 74.88

131 179 62.82 91.18 96.81 92.15 67.28 60.47 90.96 99.52 93.55 71.93

132 172 60.33 81.69 99.43 84.31 62.40 64.02 82.78 96.01 91.23 67.57

133 170 64.43 91.66 98.74 90.76 72.99 66.90 89.08 97.20 92.70 73.61

134 178 52.56 83.48 99.05 73.02 56.44 52.57 83.07 92.25 73.90 54.64

135 175 70.05 94.55 101.16 98.80 77.31 67.39 94.53 101.05 96.05 80.79

136 177 58.89 92.83 99.98 85.80 67.36 61.84 92.89 101.92 91.29 72.69

137 178 47.45 88.96 92.99 80.16 67.17 51.44 83.46 96.18 81.31 60.06

138 176 59.96 84.06 92.28 89.53 65.55 68.21 85.68 91.86 85.99 67.68

139 172 60.74 82.58 92.19 80.96 58.73 58.95 80.79 93.81 82.21 64.46

140 174 65.85 94.02 101.55 93.96 72.26 65.97 94.10 101.55 93.07 70.33

141 177 55.86 89.98 99.02 82.99 62.32 56.14 82.58 98.79 81.52 63.67

142 176 71.88 79.81 94.54 78.16 62.93 67.53 84.85 99.76 77.32 65.29

73

No H L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

143 173 68.29 85.02 100.52 94.80 72.84 65.60 90.16 101.23 91.58 74.46

144 165 62.59 89.28 98.82 87.39 69.39 59.79 87.78 92.50 91.82 71.04

145 178 64.19 93.39 96.94 92.63 71.35 67.31 94.78 96.34 94.36 71.35

146 175 73.03 92.87 96.57 89.98 84.01 72.41 93.43 98.00 90.01 83.44

147 172 60.74 82.58 92.19 80.96 58.73 58.95 80.79 98.00 82.21 64.46

148 175 70.41 89.89 101.11 88.04 70.93 66.48 92.33 101.23 88.34 66.97

149 179 64.50 88.95 97.66 88.57 71.00 66.83 92.26 98.67 90.74 68.86

150 176 71.88 79.81 94.54 78.16 62.93 67.53 84.85 99.76 77.32 65.29

Proximal inter-phalangeal joint’s width measurement in Female (n=150)

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

1 19.11 17.38 17.43 17.27 13.97 20.78 19.64 18.98 17.55 15.82

2 15.44 14.83 15.80 14.26 11.83 16.38 15.56 15.85 14.26 11.99

3 18.89 16.64 18.03 16.54 14.34 17.98 17.89 17.97 16.82 13.55

4 15.70 14.87 14.82 13.70 12.22 16.39 15.16 14.98 14.46 12.18

5 16.88 16.54 17.19 16.27 14.03 17.44 16.65 17.43 16.36 14.22

6 20.49 17.39 17.76 16.60 15.03 19.54 17.75 18.80 16.71 14.63

7 15.94 15.70 15.87 13.76 12.48 16.76 15.82 15.83 14.09 12.39

8 16.61 18.18 18.58 17.38 14.21 18.36 17.63 18.59 17.82 14.36

9 19.41 18.19 17.35 16.57 14.39 18.81 18.77 18.66 17.69 15.09

10 18.42 16.13 16.32 15.57 14.55 17.69 17.17 17.40 16.20 15.40

11 22.63 17.90 18.64 18.09 15.57 22.89 18.75 18.61 18.16 15.91

12 19.58 19.88 20.11 17.74 15.84 22.50 20.26 19.53 17.71 16.02

13 18.49 17.60 17.69 16.76 15.16 19.17 18.22 17.30 16.62 15.30

14 19.33 17.44 16.70 16.09 14.95 18.24 18.84 17.15 17.35 14.90

15 19.02 19.17 18.91 18.23 16.38 20.82 19.64 19.37 17.73 17.06

74

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

16 20.77 19.33 20.50 18.19 17.43 21.32 20.21 18.61 19.38 15.77

17 17.91 18.24 18.31 17.56 15.39 20.37 17.64 17.72 17.30 15.78

18 17.49 17.19 17.32 16.28 14.83 19.33 18.29 18.25 17.43 15.27

19 15.46 15.42 14.76 13.08 12.20 18.05 16.55 16.46 14.42 12.00

20 17.65 18.70 16.23 15.40 13.96 16.87 17.39 16.86 16.50 14.11

21 15.32 14.68 14.75 14.82 11.87 16.87 16.39 16.86 15.82 12.90

22 17.99 16.04 16.25 14.60 12.32 19.24 17.17 17.15 15.59 21.91

23 18.89 19.35 19.78 18.95 15.71 21.12 19.55 19.70 18.78 15.30

24 20.37 18.64 18.43 17.57 15.76 21.01 18.10 19.58 18.70 16.16

25 19.29 16.14 17.21 16.46 13.01 19.32 17.96 18.17 17.90 13.94

26 19.86 18.99 18.30 17.38 14.48 19.38 19.11 19.21 18.70 16.29

27 18.69 16.42 16.49 14.89 13.77 18.10 16.85 16.92 14.80 13.48

28 16.43 16.86 17.43 16.92 13.36 17.97 16.06 18.00 17.29 14.69

29 16.87 17.23 15.86 15.85 13.65 17.96 17.66 17.39 17.15 15.09

30 17.96 15.10 15.82 15.24 12.74 17.51 16.10 16.66 14.91 12.70

31 17.64 16.06 16.46 14.86 13.09 18.98 17.65 17.11 15.75 13.94

32 17.98 16.26 16.44 15.74 12.88 18.19 17.24 17.54 16.97 13.66

33 18.86 16.85 17.71 15.42 12.77 18.72 16.36 17.55 15.66 14.01

34 19.29 20.13 18.85 17.48 13.96 19.56 19.87 18.74 18.60 15.39

35 18.93 16.72 17.83 16.42 13.77 18.54 17.92 18.30 16.38 14.41

36 19.16 19.37 18.48 17.93 14.50 21.14 19.34 18.56 19.00 14.84

37 19.11 17.75 19.09 17.52 14.83 20.64 19.34 18.80 16.94 15.09

38 20.17 18.41 19.22 18.87 15.34 20.61 18.72 20.39 18.45 16.22

39 20.54 20.03 20.94 18.57 15.42 21.16 20.53 21.79 18.97 16.85

40 18.43 18.01 17.08 15.69 12.59 18.09 18.01 17.00 16.65 15.43

41 21.96 20.51 19.68 19.47 17.19 21.78 19.54 20.46 20.33 16.79

42 18.95 15.48 16.08 15.23 13.27 19.59 17.28 17.59 16.20 14.14

75

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

43 19.47 17.18 17.09 16.67 14.68 18.21 17.89 18.98 18.24 13.53

44 17.77 16.11 15.78 15.27 13.20 17.67 17.15 16.79 14.65 13.86

45 19.29 19.6 18.46 17.71 14.80 21.6 19.87 18.58 18.14 14.74

46 19.74 18.71 18.14 18.36 14.41 20.47 19.78 18.85 17.56 16.13

47 20.42 16.74 17.07 16.33 14.48 19.83 18.13 18.44 17.75 14.75

48 19.25 16.96 18.51 17.04 14.64 20.21 18.66 18.41 17.12 15.62

49 20.85 18.97 18.30 16.95 14.61 20.84 20.04 19.18 17.79 15.13

50 20.26 18.31 18.56 17.98 15.99 20.74 19.36 19.61 17.49 16.16

51 19.68 17.98 18.67 16.44 15.16 19.20 18.94 19.19 17.32 15.79

52 16.29 15.62 16.41 14.71 12.85 17.76 16.81 16.87 15.36 13.71

53 22.30 19.08 19.29 17.47 16.01 21.71 19.30 20.14 18.90 17.64

54 19.14 16.61 16.71 15.63 14.03 17.97 16.38 16.81 16.68 14.18

55

56

22.88

21.97

18.92

18.57

19.54

19.82

17.67

16.68

15.46

14.42

21.02

21.79

19.99

18.82

19.45

18.88

18.24

18.28

16.08

16.31

57 19.37 18.45 17.45 16.89 14.90 18.69 18.13 19.63 16.57 14.50

58 21.06 18.97 19.62 17.61 15.73 21.06 21.56 21.17 18.62 15.32

59 18.61 18.31 18.61 15.95 13.86 18.42 18.79 19.23 16.65 13.81

60 18.12 18.34 17.63 16.63 14.92 20.26 18.24 18.01 17.45 15.55

61 16.14 16.59 16.70 15.67 12.86 18.03 16.80 17.01 15.80 13.42

62 19.36 18.02 16.61 15.80 14.94 19.19 18.40 17.98 15.76 14.74

63 15.51 15.57 16.82 16.00 13.01 18.29 16.39 17.60 15.29 11.87

64 17.11 16.00 14.72 14.82 12.36 17.08 16.56 16.87 15.29 13.53

65 18.26 17.04 16.92 15.69 13.48 18.76 17.97 17.95 16.75 14.53

66 15.02 16.49 16.42 15.41 12.77 16.36 16.70 16.70 15.58 13.68

67 20.07 18.45 18.17 17.07 15.71 20.78 18.80 19.34 17.42 15.93

68 18.31 16.39 16.14 15.42 13.93 18.13 16.20 16.25 16.79 14.78

69 17.33 16.37 16.88 15.28 13.65 18.04 17.41 17.28 15.62 14.06

76

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

70 18.01 17.84 17.30 15.65 14.33 18.82 18.39 18.37 16.58 14.49

71 17.61 16.50 15.90 15.36 13.97 17.71 17.45 15.88 15.89 14.25

72 19.40 16.70 16.30 17.37 14.53 19.12 17.21 17.15 16.55 14.77

73 16.42 15.09 15.36 14.43 12.65 16.16 16.02 15.75 14.54 11.89

74 16.32 16.40 15.89 14.26 13.08 18.97 15.95 16.20 14.89 13.49

75 17.96 18.73 18.52 18.35 15.28 18.84 19.84 19.35 18.80 15.89

76 21.49 18.79 18.39 19.04 15.48 22.06 19.24 20.52 19.15 16.00

77 17.02 16.39 16.74 17.01 14.41 18.73 18.45 17.96 17.44 14.07

78 20.29 17.40 17.21 16.83 13.51 18.56 16.42 17.16 15.63 14.53

79 19.93 19.01 18.57 18.06 14.63 19.94 18.61 19.16 17.73 15.81

80 20.00 20.28 18.35 18.27 15.88 19.57 19.86 20.18 18.72 16.67

81 17.62 15.11 16.61 14.50 12.23 16.08 14.82 15.31 14.68 12.52

82 15.89 15.76 15.78 15.25 13.46 17.08 15.37 16.17 15.21 13.16

83 18.17 18.55 18.48 16.92 14.24 19.39 19.36 19.60 18.29 15.92

84 17.88 15.84 17.31 15.26 14.24 16.54 16.58 17.56 16.05 14.43

85 16.86 15.88 16.44 15.55 13.27 18.65 16.62 17.39 16.23 13.05

86 18.28 18.89 19.20 17.72 15.26 20.91 18.53 19.09 17.07 15.93

87 17.96 14.23 16.87 16.68 14.91 18.86 17.15 17.17 15.95 14.49

88 17.13 15.61 16.79 14.80 13.54 17.86 17.34 17.07 16.40 13.82

89 16.00 15.57 16.47 15.28 12.78 16.80 15.67 15.81 15.45 13.16

90 17.83 16.90 17.64 14.95 13.54 17.92 17.05 17.46 15.92 13.89

91 17.55 17.23 17.94 15.92 14.18 16.99 18.10 18.63 17.50 14.87

92 18.17 16.94 18.32 17.09 16.03 17.21 16.70 18.31 17.03 14.88

93 17.85 16.45 16.02 14.94 13.38 18.08 16.24 16.58 16.16 14.34

94 19.18 16.80 17.85 16.65 14.15 20.39 17.50 18.15 17.21 14.99

95 17.26 16.71 16.76 15.62 12.97 17.12 17.23 17.35 16.36 13.7

96 16.63 14.95 15.96 15.11 13.01 18.17 16.60 16.92 15.22 13.91

77

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

97 18.53 17.00 16.81 16.49 14.60 18.89 17.69 18.09 17.34 15.72

98 16.87 16.18 17.01 15.34 14.11 17.42 16.77 17.49 16.15 14.36

99 17.05 16.55 16.66 15.22 14.24 18.45 17.10 16.99 15.86 15.62

100 16.09 15.26 14.97 13.73 11.35 17.55 15.87 15.37 14.49 12.23

101 17.26 16.29 15.63 15.32 13.14 17.70 16.09 16.62 15.89 14.13

102 15.74 14.69 15.58 13.97 12.59 17.21 15.62 16.01 14.46 12.61

103 18.67 16.91 17.64 17.25 13.22 20.02 16.82 17.75 16.47 14.27

104 14.84 14.87 15.43 14.7 12.45 14.62 12.95 12.93 12.81 11.97

105 15.90 15.03 14.66 14.01 12.59 15.77 14.51 14.97 14.26 12.31

106 17.28 15.36 15.62 14.67 13.41 19.09 16.51 16.38 15.45 13.66

107 16.30 15.60 15.63 14.38 12.77 16.48 15.69 17.40 15.04 13.39

108 19.33 18.73 18.64 18.44 15.81 19.75 19.49 19.85 19.19 15.61

109 22.81 19.09 19.36 18.41 16.23 24.48 20.54 20.72 20.28 16.99

110 21.00 18.51 20.03 17.99 16.16 21.62 19.32 19.48 18.03 16.13

111 20.50 20.66 20.75 18.73 16.29 20.67 20.88 21.16 18.33 15.92

112 20.63 18.01 19.03 18.15 15.58 20.55 20.18 19.81 17.91 16.20

113 19.91 17.35 17.52 15.41 13.58 18.80 18.19 18.42 16.36 14.63

114 18.81 18.77 18.66 17.69 15.09 19.41 18.19 17.35 16.57 14.39

115 17.69 17.17 17.40 16.20 15.40 18.42 16.13 16.32 15.57 14.55

116 22.89 18.75 18.61 18.16 15.91 22.63 17.90 18.64 18.09 15.57

117 22.50 20.26 19.53 17.71 16.02 19.58 19.88 20.11 17.74 15.84

118 19.17 18.22 17.30 16.62 15.30 18.49 17.60 17.69 16.76 15.16

119 18.24 18.84 17.15 17.35 14.90 19.33 17.44 16.70 16.09 14.95

120 17.96 17.66 17.39 17.15 15.09 16.87 17.23 15.86 15.85 13.65

121 17.51 16.10 16.66 14.91 12.70 17.96 15.10 15.82 15.24 12.74

122 18.98 17.65 17.11 15.75 13.94 17.64 16.06 16.46 14.86 13.09

123 18.19 17.24 17.54 16.97 13.66 17.98 16.26 16.44 15.74 12.88

78

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

124 18.72 16.36 17.55 15.66 14.01 18.86 16.85 17.71 15.42 12.77

125 20.78 18.80 19.34 17.42 15.93 20.07 18.45 18.17 17.07 15.71

126 18.13 16.20 16.25 16.79 14.78 18.31 16.39 16.14 15.42 13.93

127 18.04 17.41 17.28 15.62 14.06 17.33 16.37 16.88 15.28 13.65

128 18.82 18.39 18.37 16.58 14.49 18.01 17.84 17.30 15.65 14.33

129 17.71 17.45 15.88 15.89 14.25 17.61 16.50 15.90 15.36 13.97

130 20.78 19.64 18.98 17.55 15.82 19.11 17.38 17.43 17.27 13.97

131 22.89 18.75 18.61 18.16 15.91 22.63 17.90 18.64 18.09 15.57

132 22.50 20.26 19.53 17.71 16.02 19.58 19.88 20.11 17.74 15.84

133 19.17 18.22 17.30 16.62 15.30 18.49 17.60 17.69 16.76 15.16

134 17.44 16.65 17.43 16.36 14.22 16.88 16.54 17.19 16.27 14.03

135 19.96 18.26 18.80 18.59 15.53 18.73 17.61 17.67 17.21 15.05

136 21.06 19.56 19.21 18.78 16.25 20.76 18.73 18.68 17.40 15.88

137 21.52 18.93 19.74 18.11 16.17 21.43 18.95 17.87 17.79 16.08

138 21.19 19.89 22.61 19.67 17.23 22.27 20.14 20.58 18.60 16.53

139 20.78 19.01 18.86 17.42 14.73 19.95 18.82 18.97 16.29 14.49

140 19.33 18.73 18.64 18.44 15.81 19.75 19.49 19.85 19.19 15.61

141 22.81 19.09 19.36 18.41 16.23 24.48 20.54 20.72 20.28 16.99

142 21.00 18.51 20.03 17.99 16.16 21.62 19.32 19.48 18.03 16.13

143 22.89 18.75 18.61 18.16 15.91 22.63 17.90 18.64 18.09 15.57

144 22.50 20.26 19.53 17.71 16.02 19.58 19.88 20.11 17.74 15.84

145 19.17 18.22 17.30 16.62 15.30 18.49 17.60 17.69 16.76 15.16

146 22.89 18.75 18.61 18.16 15.91 22.63 17.90 18.64 18.09 15.57

147 22.50 20.26 19.53 17.71 16.02 19.58 19.88 20.11 17.74 15.84

148 19.17 18.22 17.30 16.62 15.30 18.49 17.60 17.69 16.76 15.16

149 15.89 15.76 15.78 15.25 13.46 17.08 15.37 16.17 15.21 13.16

150 19.02 19.17 18.91 18.23 16.38 20.82 19.64 19.37 17.73 17.06

79

Proximal inter-phalangeal joint’s width measurement in Male (n=150)

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

1 19.33 18.73 18.64 18.44 15.81 19.75 19.49 19.85 19.19 15.61

2 22.81 19.09 19.36 18.41 16.23 24.48 20.54 20.72 20.28 16.99

3 21.00 18.51 20.03 17.99 16.16 21.62 19.32 19.48 18.03 16.13

4 20.50 20.66 20.75 18.73 16.29 20.67 20.88 21.16 18.33 15.92

5 20.63 18.01 19.03 18.15 15.58 20.55 20.18 19.81 17.91 16.2

6 19.91 17.35 17.52 15.41 13.58 18.80 18.19 18.42 16.36 14.63

7 20.84 19.14 19.88 19.36 15.35 22.46 19.95 21.32 20.09 16.8

8 19.14 18.18 19.12 19.03 14.38 21.08 19.92 20.17 18.57 15.81

9 21.12 18.53 19.11 17.27 15.39 20.76 18.07 18.25 17.12 15.83

10 18.73 17.61 17.67 17.21 15.05 19.96 18.26 18.80 18.59 15.53

11 20.76 18.73 18.68 17.40 15.88 21.06 19.56 19.21 18.78 16.25

12 21.43 18.95 17.87 17.79 16.08 21.52 18.93 19.74 18.11 16.17

13 22.27 20.14 20.58 18.60 16.53 21.19 19.89 22.61 19.67 17.23

14 19.95 18.82 18.97 16.29 14.49 20.78 19.01 18.86 17.42 14.73

15 20.50 19.41 18.97 19.15 16.36 21.59 20.21 21.08 20.51 17.67

16 21.00 18.39 18.31 18.65 14.89 21.16 18.53 19.00 18.25 15.18

17 21.57 19.59 18.99 17.51 14.46 23.37 20.20 19.82 18.23 15.48

18 16.97 15.90 16.67 16.40 14.06 17.77 17.27 16.88 15.69 14.32

19 20.48 18.86 18.33 17.69 13.54 20.94 20.47 20.55 18.86 15.23

20 21.68 19.06 19.71 18.73 16.15 21.29 18.98 19.21 17.70 16.39

21 20.83 20.13 20.15 18.92 15.91 21.41 19.83 19.70 18.95 16.04

22 19.71 18.34 18.56 17.04 15.19 19.60 18.67 19.76 17.82 14.62

23 21.87 17.64 19.22 17.44 16.41 23.55 18.69 19.65 18.51 16.11

24 16.76 15.48 16.00 15.51 12.06 17.70 16.29 17.03 14.95 12.22

25 20.51 19.64 18.39 18.03 15.04 19.91 19.72 19.18 19.00 16.15

26 21.42 18.14 17.91 16.84 13.40 21.97 19.26 19.31 17.76 14.63

80

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

27 20.50 19.41 15.59 17.41 15.34 21.58 19.51 19.87 18.31 16.64

28 22.51 19.91 20.20 18.63 16.38 21.86 21.03 20.64 18.88 18.68

29 21.55 20.36 19.77 18.57 16.05 22.12 20.72 20.38 19.44 17.57

30 21.03 19.22 20.41 18.29 16.36 23.14 20.81 21.06 19.41 16.69

31 21.36 18.21 18.14 16.01 14.30 21.53 18.53 18.66 17.56 14.96

32 19.26 19.19 18.15 16.95 15.27 21.18 19.92 19.41 17.92 16.43

33 19.11 19.83 18.83 16.70 15.20 18.86 18.46 20.21 17.99 16.43

34 20.77 20.40 19.86 18.40 17.40 21.37 20.27 20.12 18.74 16.84

35 21.55 20.49 19.66 18.09 15.76 23.05 21.33 20.69 19.42 17.00

36 21.41 19.83 19.90 18.48 17.23 21.12 20.29 20.66 19.19 17.19

37 22.13 21.43 21.41 18.78 17.21 22.07 21.18 21.45 19.26 17.05

38 19.15 17.39 17.42 16.56 13.51 19.71 19.09 19.22 16.51 14.23

39 18.95 15.48 16.08 15.23 13.27 19.59 17.28 17.59 16.20 14.14

40 21.86 20.05 20.29 18.98 16.56 22.50 20.32 20.37 20.04 16.23

41 21.75 21.49 20.92 20.20 15.84 23.99 22.42 22.48 20.24 16.83

42 20.37 20.15 20.96 19.86 16.92 21.75 20.37 21.93 19.24 16.87

43 19.26 18.90 19.45 17.25 15.62 19.34 19.59 19.85 19.13 14.93

44 20.22 20.83 20.44 19.57 16.51 22.34 21.08 22.20 20.79 15.90

45 19.90 19.70 19.69 20.31 15.35 20.74 20.03 20.72 25.06 17.18

46 18.28 18.89 19.20 17.72 15.26 20.91 18.53 19.09 17.07 15.93

47 17.96 14.23 16.87 16.68 14.91 18.86 17.15 17.17 15.95 14.49

48 17.13 15.61 16.79 14.80 13.54 17.86 17.34 17.07 16.40 13.82

49 16.00 15.57 16.47 15.28 12.78 16.80 15.67 15.81 15.45 13.16

50 17.83 16.90 17.64 14.95 13.54 17.92 17.05 17.46 15.92 13.89

51 17.55 17.23 17.94 15.92 14.18 16.99 18.10 18.63 17.50 14.87

52 18.17 16.94 18.32 17.09 16.03 17.21 16.70 18.31 17.03 14.88

53 17.85 16.45 16.02 14.94 14.38 18.08 16.24 16.58 16.16 14.34

81

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

54 19.18 16.80 17.85 16.65 14.15 20.39 17.50 18.15 17.21 14.99

55 17.26 16.71 16.76 15.62 13.97 17.12 17.23 17.35 16.36 13.70

56 16.63 14.95 15.96 15.11 13.01 18.17 16.60 16.92 15.22 13.91

57 18.53 17.00 16.81 16.49 14.60 18.89 17.69 18.09 17.34 15.72

58 16.87 16.18 17.01 15.34 14.11 17.42 16.77 17.49 16.15 14.36

59 18.01 16.55 16.66 15.22 14.24 18.45 17.10 16.99 15.86 15.62

60 16.09 15.26 14.97 13.73 13.35 17.55 15.87 15.37 14.49 13.23

61 17.26 16.29 15.63 15.32 13.55 17.70 16.09 16.62 15.89 13.37

62 15.74 14.69 15.58 13.97 12.59 17.21 15.62 16.01 14.46 12.61

63 18.67 16.91 17.64 17.25 15.22 20.02 16.82 17.75 16.47 15.27

64 14.84 14.87 15.43 14.70 13.45 14.62 12.95 12.93 12.81 13.97

65 15.90 15.03 14.66 14.01 13.59 15.77 14.51 14.97 14.26 13.31

66 17.28 15.36 15.62 14.67 13.41 19.09 16.51 16.38 15.45 13.66

67 16.30 15.60 15.63 14.38 12.77 16.48 15.69 17.40 15.04 13.39

68 21.29 18.98 19.21 17.70 16.39 21.68 19.06 19.71 18.73 16.15

69 21.41 19.83 19.70 18.95 16.04 20.83 20.13 20.15 18.92 15.91

70 19.60 18.67 19.76 17.82 15.04 19.71 18.34 18.56 17.04 15.19

71 23.55 18.69 19.65 18.51 16.11 21.87 17.64 19.22 17.44 16.41

72 17.70 16.29 17.03 14.95 14.84 16.76 15.48 16.00 15.51 14.39

73 19.91 19.72 19.18 19.00 15.15 20.51 19.64 18.39 18.03 15.04

74 21.97 19.26 19.31 17.76 14.63 21.42 18.14 17.91 16.84 14.31

75 21.58 19.51 19.87 18.31 15.64 20.50 19.41 18.43 17.41 15.34

76 21.86 19.03 20.64 18.88 16.68 22.51 19.91 20.20 18.63 16.38

77 22.12 20.72 20.38 19.44 17.57 21.55 20.36 19.77 18.57 16.05

78 23.14 20.81 21.06 19.41 16.69 21.03 19.22 20.41 18.29 16.36

79 21.53 18.53 18.66 17.56 14.96 21.36 18.21 18.14 16.01 14.30

80 19.12 17.21 17.15 16.55 14.77 19.40 16.70 16.30 17.37 14.53

82

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

81 16.16 16.02 15.75 14.54 13.89 16.42 15.09 15.36 14.43 13.65

82 18.97 15.95 16.20 14.89 14.49 16.32 16.40 15.89 14.26 14.08

83 18.84 19.84 19.35 18.80 15.89 17.96 18.73 18.52 18.35 15.28

84 22.06 19.24 20.52 19.15 16.00 21.49 18.79 18.39 19.04 15.48

85 18.73 18.45 17.96 17.44 14.07 17.02 16.39 16.74 17.01 14.41

86 18.56 16.42 17.16 15.63 14.53 20.29 17.40 17.21 16.83 13.51

87 19.94 18.61 19.16 17.73 15.81 19.93 19.01 18.57 18.06 14.63

88 16.57 19.86 20.18 18.72 16.67 16.00 19.28 20.35 18.27 15.88

89 16.08 14.82 15.31 14.68 14.52 15.62 15.11 16.61 14.50 14.23

90 17.08 15.37 16.17 15.21 14.16 15.89 15.76 15.78 15.25 14.46

91 19.39 19.36 19.60 18.29 15.92 18.17 18.55 18.48 16.92 14.24

92 16.54 16.58 17.56 16.05 14.43 17.88 15.84 17.31 15.26 14.24

93 18.65 16.62 17.39 16.23 15.05 16.86 15.88 16.44 15.55 15.27

94 20.91 18.53 19.09 17.07 15.93 18.28 18.89 19.20 17.72 15.26

95 18.86 17.15 17.17 15.95 14.49 17.96 14.23 16.87 16.68 14.91

96 17.86 17.34 17.07 16.40 13.82 17.13 15.61 16.79 14.80 13.54

97 16.80 15.67 15.81 15.45 14.16 16.00 15.57 16.47 15.28 14.78

98 17.92 17.05 17.46 15.92 13.89 17.83 16.90 17.64 14.95 13.54

99 16.99 18.10 18.63 17.50 14.87 17.55 17.23 17.94 15.92 14.18

100 17.21 16.70 18.31 17.03 14.88 18.17 16.94 18.32 17.09 16.03

101 18.08 16.24 16.58 16.16 14.34 17.85 16.45 16.02 14.94 13.38

102 20.39 17.50 18.15 17.21 14.99 19.18 16.80 17.85 16.65 14.15

103 17.12 17.23 17.35 16.36 13.70 17.26 16.71 16.76 15.62 12.97

104 18.17 16.60 16.92 15.22 14.91 16.63 14.95 15.96 15.11 14.01

105 18.89 17.69 18.09 17.34 15.72 18.53 17.00 16.81 16.49 14.60

106 17.42 16.77 17.49 16.15 14.36 16.87 16.18 17.01 15.34 14.11

107 18.45 17.10 16.99 15.86 15.62 17.05 16.55 16.66 15.22 14.24

83

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

108 17.55 15.87 15.37 14.49 14.23 16.09 15.26 14.97 14.73 14.35

109 17.70 16.09 16.62 15.89 14.13 17.26 16.29 15.63 15.32 13.14

110 17.21 15.62 16.01 14.46 14.61 15.74 14.69 15.58 14.97 14.59

111 20.02 16.82 17.75 16.47 14.27 18.67 16.91 17.64 17.25 13.22

112 14.62 12.95 12.93 12.81 11.97 14.84 14.87 15.43 14.7 12.45

113 15.77 14.51 14.97 14.26 12.31 15.90 15.03 14.66 14.01 12.59

114 19.09 16.51 16.38 15.45 13.66 17.28 15.36 15.62 14.67 13.41

115 16.48 15.69 17.40 15.04 15.39 16.30 15.60 15.63 14.38 15.77

116 19.75 19.49 19.85 19.19 15.61 19.33 18.73 18.64 18.44 15.81

117 24.48 20.54 20.72 20.28 16.98 22.81 19.09 19.36 18.41 16.23

118 21.62 19.32 19.48 18.03 16.13 21.00 18.51 20.03 17.99 16.16

119 20.67 20.88 21.16 18.33 15.92 20.50 20.66 20.75 18.73 16.29

120 20.55 20.18 19.81 17.91 16.20 20.63 18.01 19.03 18.15 15.58

121 18.80 18.19 18.42 16.36 14.63 19.91 17.35 17.52 15.41 13.58

122 19.41 18.19 17.35 16.57 14.39 18.81 18.77 18.66 17.69 15.09

123 18.42 16.13 16.32 15.57 14.55 17.69 17.17 17.40 16.20 15.40

124 22.63 17.90 18.64 18.09 15.57 22.89 18.75 18.61 18.16 15.91

125 19.58 19.88 20.11 17.74 15.84 22.50 20.26 19.53 17.71 16.02

126 18.49 17.60 17.69 16.76 15.16 19.17 18.22 17.30 16.62 15.30

127 19.33 17.44 16.70 16.09 14.95 18.24 18.84 17.15 17.35 14.90

128 16.87 17.23 15.86 15.85 13.65 17.96 17.66 17.39 17.15 15.09

129 17.96 15.10 15.82 15.24 14.74 17.51 16.10 16.66 14.91 15.70

130 17.64 16.06 16.46 14.86 15.09 18.98 17.65 17.11 15.75 15.94

131 17.98 16.26 16.44 15.74 15.88 18.19 17.24 17.54 16.97 15.66

132 18.86 16.85 17.71 15.42 15.77 18.72 16.36 17.55 15.66 14.01

133 20.07 18.45 18.17 17.07 15.71 20.78 18.80 19.34 17.42 15.93

134 18.31 16.39 16.14 15.42 15.93 18.13 16.20 16.25 16.79 15.78

84

No L1 L2 L3 L4 L5 R1 R2 R3 R4 R5

135 17.33 16.37 16.88 15.28 13.65 18.04 17.41 17.28 15.62 14.06

136 18.01 17.84 17.30 15.65 14.33 18.82 18.39 18.37 16.58 14.49

137 17.61 16.50 15.90 15.36 13.97 17.71 17.45 15.88 15.89 14.25

138 19.11 17.38 17.43 17.27 13.97 20.78 19.64 18.98 17.55 15.82

139 15.44 14.83 15.80 14.26 11.83 16.38 15.56 15.85 14.26 11.99

140 18.89 16.64 18.03 16.54 14.34 17.98 17.89 17.97 16.82 13.55

141 15.70 14.87 14.82 13.70 12.22 16.39 15.16 14.98 14.46 12.18

142 16.88 16.54 17.19 16.27 14.03 17.44 16.65 17.43 16.36 14.22

143 18.73 17.61 17.67 17.21 15.05 19.96 18.26 17.80 18.59 15.53

144 19.76 18.73 19.68 17.40 15.88 19.06 18.56 19.21 17.78 16.25

145 21.43 18.95 18.33 17.79 16.08 21.52 18.93 19.74 18.11 16.17

146 19.27 20.14 20.58 18.60 16.53 21.19 19.89 22.61 19.67 17.23

147 19.95 18.82 18.97 16.29 14.49 20.78 19.01 18.86 17.42 14.73

148 19.75 19.49 19.85 19.19 15.61 19.33 18.73 18.64 18.44 15.81

149 24.48 20.54 20.72 20.28 16.98 22.81 19.09 19.36 18.41 16.23

150 21.22 18.98 19.48 18.03 16.13 21.01 18.51 20.03 17.99 16.16

85

Estimation stature in Female

One-Sample Test

Test Value = 0

t df

Sig. (2-

tailed)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

L1 156.791 149 .000 62.11007 61.3273 62.8928

L2 200.902 149 .000 87.45587 86.5957 88.3161

L3 209.176 149 .000 94.54507 93.6519 95.4382

L4 164.071 149 .000 87.85800 86.7999 88.9161

L5 146.447 149 .000 68.67513 67.7485 69.6018

R1 148.653 149 .000 62.60707 61.7748 63.4393

R2 195.645 149 .000 87.52960 86.6456 88.4136

R3 211.162 149 .000 95.21067 94.3197 96.1016

R4 191.592 149 .000 88.55420 87.6409 89.4675

R5 140.069 149 .000 70.54667 69.5514 71.5419

86

Paired Samples Test female

Paired Differences

t df

Sig.

(2-

tailed

) Mean

Std.

Deviatio

n

Std.

Error

Mean

95% Confidence

Interval of the

Difference

Lower Upper

Pair 1 L1 -

R1

-.49575 4.77960 .38768 -1.26172 .27022 -1.279 151 .203

Pair 2 L2 -

R2

-.07422 2.91025 .23605 -.54061 .39217 -.314 151 .754

Pair 3 L3 -

R3

-.66113 3.22613 .26167 -1.17815 -.14412 -2.527 151 .013

Pair 4 L4 -

R4

-.68571 3.79168 .30755 -1.29336 -.07807 -2.230 151 .027

Pair 5 L5-

R5

-1.86203 4.73445 .38401 -2.62076 -1.10329 -4.849 151 .000

Regression analysis from L1

Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .406 .165 .160 5.47121

87

ANOVAb

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 876.824 1 876.824 29.292 .000

Residual 4430.250 148 29.934

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 127.498 5.755 22.153 .000

L1 .500 .092 .406 5.412 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .493 .243 .238 5.20850

88

ANOVAb

Model

Sum of


1 Regression 1292.067 1 1292.067 47.628 .000

Residual 4015.006 148 27.128

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 110.249 7.012 15.722 .000

L2 .552 .080 .493 6.901 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .571 .326 .321 4.91713

89

ANOVAb

Model

Sum of


1 Regression 1728.702 1 1728.702 71.498 .000

Residual 3578.372 148 24.178

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 100.379 6.892 14.565 .000

L3 .615 .073 .571 8.456 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .478 .228 .223 5.26003

90

ANOVAb

Model

Sum of


1 Regression 1212.220 1 1212.220 43.813 .000

Residual 4094.853 148 27.668

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 120.343 5.789 20.789 .000

L4 .435 .066 .478 6.619 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .415 .172 .166 5.44866

91

ANOVAb

Model

Sum of


1 Regression 913.259 1 913.259 30.762 .000

Residual 4393.814 148 29.688

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 128.950 5.356 24.076 .000

L5 .431 .078 .415 5.546 .000

Regression analysis from R1

Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .395 .156 .151 5.50012

92

ANOVAb

Model

Sum of


1 Regression 829.885 1 829.885 27.433 .000

Residual 4477.189 148 30.251

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 129.909 5.487 23.674 .000

R1 .458 .087 .395 5.238 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .506 .256 .251 5.16530

93

ANOVAb

Model

Sum of


1 Regression 1358.388 1 1358.388 50.913 .000

Residual 3948.686 148 26.680

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 110.321 6.773 16.289 .000

R2 .551 .077 .506 7.135 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .538 .290 .285 5.04597

94

ANOVAb

Model

Sum of


1 Regression 1538.718 1 1538.718 60.432 .000

Residual 3768.355 148 25.462

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 103.147 7.139 14.448 .000

R3 .582 .075 .538 7.774 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .526 .277 .272 5.09275

95

ANOVAb

Model

Sum of


1 Regression 1468.531 1 1468.531 56.621 .000

Residual 3838.542 148 25.936

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 109.442 6.540 16.735 .000

R4 .555 .074 .526 7.525 .000


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .253 .064 .058 5.79345

96

ANOVAb

Model

Sum of


1 Regression 339.586 1 339.586 10.118 .002

Residual 4967.487 148 33.564

Total 5307.073 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 141.288 5.449 25.931 .000

R5 .245 .077 .253 3.181 .002

Estimation stature in Male

One-Sample Test

Test Value = 0

t df

Sig. (2-

tailed)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

L1 159.196 149 .000 64.42347 63.6238 65.2231

L2 190.810 149 .000 90.10987 89.1767 91.0430

L3 300.867 149 .000 99.14147 98.4903 99.7926

97

L4 182.584 149 .000 90.74593 89.7638 91.7280

L5 142.974 149 .000 71.30407 70.3186 72.2895

R1 175.812 149 .000 64.94700 64.2170 65.6770

R2 202.513 149 .000 90.42940 89.5470 91.3118

R3 276.753 149 .000 99.38627 98.6767 100.0959

R4 180.990 149 .000 91.07300 90.0787 92.0673

R5 114.126 149 .000 70.93573 69.7075 72.1639

Paired Samples Test

Paired Differences

t df

Sig.

(2-

tailed

) Mean

Std.

Deviatio

n

Std.

Error

Mean

95% Confidence

Interval of the

Difference

Lower Upper

Pair 1 L1 - R1 -.51112 4.35566 .35099 -1.20453 .18229 -1.456 153 .147

Pair 2 L2 - R2 -.31129 2.83331 .22831 -.76235 .13976 -1.363 153 .175

Pair 3 L3 - R3 -.24625 2.34899 .18929 -.62021 .12770 -1.301 153 .195

Pair 4 L4 - R4 -.32380 2.98365 .24043 -.79879 .15119 -1.347 153 .180

Pair 5 L5 - R5 .34401 5.48195 .44175 -.52870 1.21673 .779 153 .437


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .074 .005 -.001 6.08541

98

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 30.064 1 30.064 .812 .369

Residual 5480.769 148 37.032

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 167.195 6.499 25.726 .000

L1 .091 .101 .074 .901 .369


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .091 .008 .002 6.07669

99

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 45.770 1 45.770 1.240 .267

Residual 5465.063 148 36.926

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 164.399 7.772 21.154 .000

L2 .096 .086 .091 1.113 .267


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .136 .019 .012 6.04514

100

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 102.366 1 102.366 2.801 .096

Residual 5408.467 148 36.544

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 152.672 12.176 12.539 .000

L3 .205 .123 .136 1.674 .096


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .013 .000 -.007 6.10155

101

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression .949 1 .949 .025 .873

Residual 5509.884 148 37.229

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 174.223 7.468 23.328 .000

L4 -.013 .082 -.013 -.160 .873


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .055 .003 -.004 6.09275

102

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 16.833 1 16.833 .453 .502

Residual 5494.000 148 37.122

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 169.110 5.848 28.917 .000

L5 .055 .082 .055 .673 .502


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .006 .000 -.007 6.10195

103

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression .227 1 .227 .006 .938

Residual 5510.606 148 37.234

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 172.473 7.193 23.977 .000

R1 .009 .110 .006 .078 .938


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .089 .008 .001 6.07803

104

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 43.343 1 43.343 1.173 .280

Residual 5467.491 148 36.943

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 164.115 8.248 19.897 .000

R2 .099 .091 .089 1.083 .280


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .114 .013 .006 6.06217

105

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 71.844 1 71.844 1.955 .164

Residual 5438.989 148 36.750

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 157.342 11.233 14.007 .000

R3 .158 .113 .114 1.398 .164


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .030 .001 -.006 6.09932

106

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 4.985 1 4.985 .134 .715

Residual 5505.848 148 37.202

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 157.342 7.401 23.745 .000

R4 -.030 .081 -.030 -.366 .715


Model Summary

Model R

R

Square

Adjusted

R

Square

Std.

Error of

the

Estimate

1 .023 .001 -.006 6.10040

107

ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regression 3.034 1 3.034 .082 .776

Residual 5507.799 148 37.215

Total 5510.833 149

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 171.704 4.684 36.661 .000

R5 .019 .066 .023 .286 .776

108

Sexual determination from proximal inter-phalangeal joint’s width.

One-Sample Statistics

Female Male

Mean

Std.

Deviation Mean

Std.

Deviation

L1 18.8234 1.95583 19.2302 2.03458

L2 17.5127 1.51726 17.8250 1.78791

L3 17.6145 1.45912 18.0599 1.71369

L4 16.5479 1.39633 16.9095 1.62957

L5 14.4278 1.27863 14.9664 1.19927

R1 19.1091 1.78263 19.3773 2.17182

R2 17.8202 1.51374 17.9884 1.80885

R3 17.9700 1.47822 18.2849 1.83855

R4 16.8129 1.40519 17.1355 1.76920

R5 14.7391 1.39727 15.0943 1.26905

109

Casewise : Prediction of sexual determination from proximal inter-phalangeal joint’s width.

Analysis Case Processing Summary

Unweighted Cases N Percent

Valid 300 100.0

Excluded Missing or out-of-range group codes 0 .0

At least one missing discriminating

variable

0 .0

Both missing or out-of-range group

codes and at least one missing

discriminating variable

0 .0

Total 0 .0

Total 300 100.0

Group Statistics

sex

Valid N (listwise)

Unweighted Weighted

1.00 L1 150 150.000

L2 150 150.000

L3 150 150.000

L4 150 150.000

L5

R1

150

150

150.000

150.000

110

R2 150 150.000

R3 150 150.000

R4 150 150.000

R5 150 150.000

2.00 L1 150 150.000

L2 150 150.000

L3 150 150.000

L4 150 150.000

L5 150 150.000

R1 150 150.000

R2 150 150.000

R3 150 150.000

R4 150 150.000

R5 150 150.000

Total L1 300 300.000

L2 300 300.000

L3 300 300.000

L4 300 300.000

L5 300 300.000

R1 300 300.000

R2 300 300.000

R3 300 300.000

R4 300 300.000

R5 300 300.000

111

Analysis 1

Summary of Canonical Discriminant Functions

Eigenvalues

Function Eigenvalue % of Variance Cumulative %

Canonical

Correlation

1 .080a 100.0 100.0 .272

a. First 1 canonical discriminant functions were used in the analysis.

Wilks' Lambda

Test of

Function(s)

Wilks'

Lambda Chi-square df Sig.

1 .926 22.466 10 .013

Standardized Canonical Discriminant Function Coefficients

Function

1

L1 -.140

L2 -.492

L3 .611

L4 -.502

L5 1.320

R1 -.112

R2 -.946

R3 .363

R4 .373

R5 .096

112

Structure Matrix

Function

1

L5กอย .772

L3 .497

R5กอย .473

L4 .423

L1โปง .362

R4 .359

R3 .335

L2 .335

R1โปง .240

R2 .179

Pooled within-groups correlations between discriminating variables and standardized canonical

discriminant functions

Variables ordered by absolute size of correlation within function.

Functions at Group Centroids

sex

Function

1

1.00 -.281

2.00 .281

Unstandardized canonical discriminant functions evaluated at group

means

113

Classification Statistics

Classification Processing Summary

Processed 300

Excluded Missing or

out-of-range

group codes

0

At least one

missing

discriminating

variable

0

Used in Output 300

Prior Probabilities for Groups

sex Prior

Cases Used in Analysis

Unweighted Weighted

1.00 .500 150 150.000

2.00 .500 150 150.000

Total 1.000 300 300.000

114

Casewise Statistics

Case

No.

Actu

al

Grou

p

Highest Group Second Highest Group

Discrimi

nant

Scores

Predict

ed

Group

P(D>d |

G=g)

P(G

=g |

D=d

)

Square

d

Mahala

nobis

Distanc

e to

Centroi

d Group

P(G=g |

D=d)

Squared

Mahalano

bis

Distance

to

Centroid

Function

1

p df

Ori

gin

al

1 1 1 .151 1 .724 2.058 2 .276 3.989 -1.716

2 1 1 .135 1 .731 2.229 2 .269 4.225 -1.774

3 1 1 .792 1 .502 .070 2 .498 .089 -.018

4 1 1 .229 1 .697 1.444 2 .303 3.113 -1.483

5 1 2** .892 1 .521 .018 1 .479 .183 .146

6 1 2** .841 1 .567 .040 1 .433 .583 .482

7 1 1 .277 1 .683 1.180 2 .317 2.719 -1.367

8 1 2** .804 1 .505 .062 1 .495 .099 .033

9 1 1 .594 1 .613 .284 2 .387 1.200 -.814

10 1 2** .951 1 .548 .004 1 .452 .389 .342

11 1 2** .963 1 .533 .002 1 .467 .266 .235

12 1 2** .854 1 .514 .034 1 .486 .143 .097

13 1 2** .836 1 .510 .043 1 .490 .126 .074

14 1 1 .819 1 .571 .052 2 .429 .626 -.510

15 1 2** .611 1 .609 .259 1 .391 1.148 .790

115

16 1 2** .063 1 .769 3.448 1 .231 5.854 2.138

17 1 2** .684 1 .596 .166 1 .404 .941 .689

18 1 2** .995 1 .539 .000 1 .461 .310 .276

19 1 1 .077 1 .760 3.133 2 .240 5.441 -2.051

20 1 1 .363 1 .662 .828 2 .338 2.168 -1.191

21 1 1 .067 1 .767 3.366 2 .233 5.747 -2.116

22 1 1 .223 1 .699 1.483 2 .301 3.170 -1.499

23 1 2** .942 1 .550 .005 1 .450 .403 .353

24 1 2** .310 1 .675 1.031 1 .325 2.490 1.297

25 1 1 .266 1 .687 1.237 2 .313 2.805 -1.394

26 1 1 .695 1 .594 .153 2 .406 .911 -.673

27 1 1 .665 1 .599 .187 2 .401 .991 -.714

28 1 1 .836 1 .510 .043 2 .490 .126 -.074

29 1 1 .359 1 .662 .841 2 .338 2.190 -1.199

30 1 1 .277 1 .684 1.183 2 .316 2.724 -1.369

31 1 1 .236 1 .695 1.404 2 .305 3.055 -1.466

32 1 1 .248 1 .692 1.333 2 .308 2.949 -1.436

33 1 1 .469 1 .638 .525 2 .362 1.657 -1.006

34 1 1 .090 1 .753 2.879 2 .247 5.106 -1.978

35 1 1 .671 1 .598 .181 2 .402 .975 -.706

36 1 1 .341 1 .667 .907 2 .333 2.295 -1.234

37 1 1 .897 1 .558 .017 2 .442 .480 -.411

38 1 2** .751 1 .583 .101 1 .417 .775 .599

39 1 2** .944 1 .549 .005 1 .451 .400 .351

40 1 1 .025 1 .806 5.054 2 .194 7.900 -2.529

41 1 2** .138 1 .729 2.195 1 .271 4.179 1.763

42 1 1 .434 1 .645 .612 2 .355 1.808 -1.063

43 1 2** .996 1 .539 .000 1 .461 .311 .277

116

44 1 1 .143 1 .727 2.141 2 .273 4.105 -1.745

45 1 1 .240 1 .694 1.382 2 .306 3.021 -1.457

46 1 1 .119 1 .738 2.427 2 .262 4.497 -1.839

47 1 1 .887 1 .520 .020 2 .480 .177 -.140

48 1 1 .815 1 .507 .055 2 .493 .108 -.048

49 1 1 .277 1 .684 1.181 2 .316 2.721 -1.368

50 1 2** .760 1 .582 .093 1 .418 .753 .586

51 1 2** .781 1 .578 .078 1 .422 .708 .560

52 1 1 .424 1 .648 .640 2 .352 1.856 -1.081

53 1 2** .350 1 .665 .872 1 .335 2.240 1.215

54 1 2** .820 1 .508 .052 1 .492 .113 .054

55 1 1 .858 1 .514 .032 2 .486 .147 -.102

56 1 1 .844 1 .512 .038 2 .488 .134 -.085

57 1 1 .884 1 .519 .021 2 .481 .174 -.136

58 1 1 .884 1 .519 .021 2 .481 .174 -.135

59 1 1 .557 1 .620 .345 2 .380 1.323 -.869

60 1 1 .827 1 .509 .048 2 .491 .118 -.062

61 1 1 .242 1 .693 1.368 2 .307 3.000 -1.451

62 1 1 .720 1 .589 .129 2 .411 .849 -.640

63 1 1 .542 1 .623 .372 2 .377 1.376 -.892

64 1 1 .043 1 .786 4.105 2 .214 6.702 -2.307

65 1 1 .362 1 .662 .832 2 .338 2.174 -1.193

66 1 1 .259 1 .688 1.272 2 .312 2.858 -1.409

67 1 2** .724 1 .588 .125 1 .412 .839 .635

68 1 1 .808 1 .505 .059 2 .495 .102 -.038

69 1 1 .666 1 .599 .187 2 .401 .990 -.713

70 1 1 .795 1 .576 .068 2 .424 .677 -.542

71 1 1 .433 1 .646 .615 2 .354 1.815 -1.066

117

72 1 1 .719 1 .589 .129 2 .411 .850 -.641

73 1 1 .229 1 .697 1.446 2 .303 3.116 -1.484

74 1 1 .489 1 .634 .478 2 .366 1.573 -.973

75 1 1 .940 1 .529 .006 2 .471 .237 -.206

76 1 1 .804 1 .505 .062 2 .495 .099 -.033

77 1 1 .774 1 .579 .083 2 .421 .723 -.569

78 1 1 .348 1 .665 .879 2 .335 2.251 -1.219

79 1 1 .701 1 .593 .147 2 .407 .896 -.665

80 1 1 .812 1 .506 .057 2 .494 .105 -.043

81 1 1 .538 1 .624 .379 2 .376 1.388 -.897

82 1 1 .965 1 .533 .002 2 .467 .269 -.237

83 1 1 .721 1 .589 .127 2 .411 .846 -.638

84 1 2** .504 1 .630 .445 1 .370 1.513 .949

85 1 1 .682 1 .596 .167 2 .404 .945 -.691

86 1 2** .953 1 .548 .003 1 .452 .387 .340

87 1 2** .512 1 .629 .430 1 .371 1.486 .937

88 1 1 .987 1 .542 .000 2 .458 .335 -.298

89 1 1 .580 1 .615 .306 2 .385 1.244 -.834

90 1 1 .974 1 .544 .001 2 .456 .354 -.314

91 1 2** .963 1 .533 .002 1 .467 .267 .235

92 1 2** .020 1 .813 5.421 1 .187 8.358 2.610

93 1 1 .732 1 .587 .117 2 .413 .819 -.624

94 1 1 .836 1 .511 .043 2 .489 .127 -.075

95 1 1 .274 1 .684 1.197 2 .316 2.745 -1.375

96 1 1 .502 1 .631 .450 2 .369 1.522 -.952

97 1 2** .849 1 .513 .036 1 .487 .138 .091

98 1 2** .839 1 .568 .041 1 .432 .586 .484

99 1 2** .835 1 .510 .043 1 .490 .126 .074

118

100 1 1 .009 1 .835 6.740 2 .165 9.978 -2.878

101 1 1 .455 1 .641 .559 2 .359 1.717 -1.029

102 1 1 .544 1 .622 .368 2 .378 1.368 -.888

103 1 1 .335 1 .668 .931 2 .332 2.333 -1.246

104 1 1 .627 1 .606 .236 2 .394 1.100 -.768

105 1 1 .503 1 .631 .448 2 .369 1.517 -.950

106 1 1 .631 1 .606 .231 2 .394 1.088 -.762

107 1 1 .730 1 .587 .119 2 .413 .824 -.626

108 1 2** .745 1 .584 .105 1 .416 .788 .606

109 1 2** .698 1 .593 .150 1 .407 .904 .669

110 1 2** .315 1 .673 1.010 1 .327 2.457 1.286

111 1 2** .871 1 .562 .026 1 .438 .525 .443

112 1 2** .800 1 .504 .064 1 .496 .095 .027

113 1 1 .425 1 .647 .638 2 .353 1.853 -1.080

114 1 1 .931 1 .552 .007 2 .448 .421 -.368

115 1 2** .308 1 .675 1.041 1 .325 2.506 1.302

116 1 2** .636 1 .605 .223 1 .395 1.072 .754

117 1 2** .983 1 .536 .000 1 .464 .293 .260

118 1 2** .917 1 .554 .011 1 .446 .445 .385

119 1 1 .602 1 .611 .271 2 .389 1.174 -.802

120 1 1 .892 1 .520 .018 2 .480 .182 -.146

121 1 1 .600 1 .612 .276 2 .388 1.183 -.806

122 1 1 .747 1 .584 .104 2 .416 .785 -.604

123 1 1 .530 1 .625 .395 2 .375 1.420 -.910

124 1 1 .830 1 .509 .046 2 .491 .122 -.067

125 1 2** .513 1 .629 .428 1 .371 1.481 .935

126 1 2** .780 1 .500 .078 1 .500 .080 .002

127 1 1 .903 1 .522 .015 2 .478 .195 -.160

119

128 1 1 .756 1 .582 .096 2 .418 .762 -.591

129 1 1 .580 1 .615 .306 2 .385 1.245 -.835

130 1 2** .597 1 .612 .279 1 .388 1.191 .810

131 1 2** .636 1 .605 .223 1 .395 1.072 .754

132 1 2** .983 1 .536 .000 1 .464 .293 .260

133 1 2** .917 1 .554 .011 1 .446 .445 .385

134 1 2** .948 1 .549 .004 1 .451 .394 .346

135 1 2** .779 1 .578 .079 1 .422 .711 .562

136 1 2** .800 1 .575 .064 1 .425 .665 .534

137 1 2** .607 1 .610 .264 1 .390 1.159 .795

138 1 2** .040 1 .788 4.229 1 .212 6.860 2.338

139 1 1 .544 1 .622 .368 2 .378 1.367 -.888

140 1 2** .745 1 .584 .105 1 .416 .788 .606

141 1 2** .698 1 .593 .150 1 .407 .904 .669

142 1 2** .315 1 .673 1.010 1 .327 2.457 1.286

143 1 2** .636 1 .605 .223 1 .395 1.072 .754

144 1 2** .983 1 .536 .000 1 .464 .293 .260

145 1 2** .917 1 .554 .011 1 .446 .445 .385

146 1 2** .636 1 .605 .223 1 .395 1.072 .754

147 1 2** .983 1 .536 .000 1 .464 .293 .260

148 1 2** .917 1 .554 .011 1 .446 .445 .385

149 1 1 .965 1 .533 .002 2 .467 .269 -.237

150 1 2** .611 1 .609 .259 1 .391 1.148 .790

151 2 2 .745 1 .584 .105 1 .416 .788 .606

152 2 2 .698 1 .593 .151 1 .407 .904 .669

153 2 2 .315 1 .673 1.010 1 .327 2.457 1.286

154 2 2 .871 1 .562 .026 1 .438 .525 .443

155 2 2 .800 1 .504 .064 1 .496 .095 .027

120

156 2 1** .425 1 .647 .638 2 .353 1.853 -1.080

157 2 2 .985 1 .537 .000 1 .463 .296 .263

158 2 1** .396 1 .654 .721 2 .346 1.994 -1.131

159 2 2 .756 1 .583 .097 1 .417 .763 .592

160 2 2 .814 1 .572 .055 1 .428 .636 .516

161 2 2 .722 1 .589 .126 1 .411 .843 .637

162 2 2 .764 1 .581 .090 1 .419 .745 .582

163 2 2 .093 1 .751 2.823 1 .249 5.030 1.961

164 2 1** .819 1 .571 .052 2 .429 .627 -.510

165 2 2 .465 1 .639 .533 1 .361 1.672 1.012

166 2 1** .783 1 .578 .076 2 .422 .702 -.556

167 2 1** .171 1 .717 1.871 2 .283 3.727 -1.649

168 2 1** .811 1 .573 .057 2 .427 .643 -.520

169 2 1** .036 1 .792 4.388 2 .208 7.063 -2.376

170 2 2 .610 1 .610 .260 1 .390 1.151 .791

171 2 2 .990 1 .538 .000 1 .462 .303 .269

172 2 2 .804 1 .574 .062 1 .426 .658 .530

173 2 2 .083 1 .757 3.009 1 .243 5.278 2.016

174 2 1** .054 1 .776 3.701 2 .224 6.182 -2.205

175 2 1** .592 1 .613 .288 2 .387 1.208 -.818

176 2 1** .055 1 .775 3.681 2 .225 6.156 -2.200

177 2 1** .332 1 .669 .941 2 .331 2.349 -1.251

178 2 2 .824 1 .570 .049 1 .430 .616 .504

179 2 2 .853 1 .514 .034 1 .486 .143 .096

180 2 2 .408 1 .651 .684 1 .349 1.932 1.109

181 2 1** .734 1 .586 .115 2 .414 .814 -.621

182 2 1** .862 1 .564 .030 2 .436 .542 -.455

183 2 2 .615 1 .609 .254 1 .391 1.137 .785

121

184 2 2 .158 1 .722 1.991 1 .278 3.896 1.692

185 2 1** .818 1 .571 .053 2 .429 .628 -.511

186 2 2 .111 1 .742 2.540 1 .258 4.651 1.875

187 2 2 .251 1 .691 1.318 1 .309 2.927 1.429

188 2 1** .103 1 .746 2.663 2 .254 4.816 -1.913

189 2 1** .434 1 .645 .612 2 .355 1.808 -1.063

190 2 2 .459 1 .640 .547 1 .360 1.697 1.021

191 2 1** .441 1 .644 .595 2 .356 1.779 -1.053

192 2 2 .169 1 .718 1.895 1 .282 3.761 1.658

193 2 2 .493 1 .633 .469 1 .367 1.557 .966

194 2 2 .575 1 .616 .314 1 .384 1.261 .842

195 2 2 .546 1 .622 .365 1 .378 1.361 .885

196 2 2 .953 1 .548 .003 1 .452 .387 .340

197 2 2 .512 1 .629 .430 1 .371 1.486 .937

198 2 1** .987 1 .542 .000 2 .458 .335 -.298

199 2 1** .580 1 .615 .306 2 .385 1.244 -.834

200 2 1** .974 1 .544 .001 2 .456 .354 -.314

201 2 2 .963 1 .533 .002 1 .467 .267 .235

202 2 2 .020 1 .813 5.421 1 .187 8.358 2.610

203 2 2 .873 1 .562 .025 1 .438 .522 .441

204 2 1** .836 1 .511 .043 2 .489 .127 -.075

205 2 1** .977 1 .544 .001 2 .456 .351 -.311

206 2 1** .502 1 .631 .450 2 .369 1.522 -.952

207 2 2 .849 1 .513 .036 1 .487 .138 .091

208 2 2 .839 1 .568 .041 1 .432 .586 .484

209 2 2 .783 1 .501 .076 1 .499 .083 .007

210 2 1** .693 1 .594 .156 2 .406 .917 -.676

211 2 1** .715 1 .590 .134 2 .410 .862 -.647

122

212 2 1** .544 1 .622 .368 2 .378 1.368 -.888

213 2 2 .500 1 .631 .454 1 .369 1.529 .955

214 2 2 .873 1 .562 .025 1 .438 .521 .441

215 2 2 .924 1 .526 .009 1 .474 .218 .186

216 2 1** .631 1 .606 .231 2 .394 1.088 -.762

217 2 1** .730 1 .587 .119 2 .413 .824 -.626

218 2 2 .219 1 .701 1.513 1 .299 3.213 1.511

219 2 2 .949 1 .531 .004 1 .469 .249 .217

220 2 2 .984 1 .537 .000 1 .463 .295 .261

221 2 2 .244 1 .693 1.360 1 .307 2.988 1.447

222 2 2 .186 1 .712 1.751 1 .288 3.556 1.604

223 2 1** .376 1 .658 .783 2 .342 2.096 -1.166

224 2 1** .534 1 .624 .387 2 .376 1.404 -.904

225 2 1** .927 1 .527 .008 2 .473 .222 -.190

226 2 2 .225 1 .699 1.474 1 .301 3.157 1.495

227 2 2 .305 1 .676 1.050 1 .324 2.520 1.306

228 2 2 .302 1 .677 1.067 1 .323 2.546 1.314

229 2 1** .698 1 .593 .151 2 .407 .904 -.669

230 2 2 .950 1 .548 .004 1 .452 .390 .344

231 2 2 .951 1 .531 .004 1 .469 .252 .220

232 2 2 .864 1 .515 .029 1 .485 .153 .110

233 2 2 .771 1 .580 .085 1 .420 .730 .573

234 2 2 .543 1 .623 .370 1 .377 1.372 .890

235 2 1** .896 1 .558 .017 2 .442 .481 -.412

236 2 2 .952 1 .531 .004 1 .469 .252 .221

237 2 2 .688 1 .595 .161 1 .405 .929 .683

238 2 2 .066 1 .768 3.392 1 .232 5.781 2.123

239 2 2 .263 1 .688 1.254 1 .312 2.832 1.401

123

240 2 2 .775 1 .579 .082 1 .421 .720 .567

241 2 2 .715 1 .590 .133 1 .410 .860 .646

242 2 2 .503 1 .631 .449 1 .369 1.519 .951

243 2 2 .302 1 .677 1.068 1 .323 2.547 1.315

244 2 2 .347 1 .665 .884 1 .335 2.259 1.222

245 2 2 .139 1 .729 2.185 1 .271 4.165 1.760

246 2 1** .891 1 .559 .019 2 .441 .489 -.418

247 2 2 .779 1 .578 .079 1 .422 .711 .562

248 2 1** .824 1 .570 .050 2 .430 .617 -.504

249 2 2 .916 1 .554 .011 1 .446 .446 .387

250 2 2 .243 1 .693 1.361 1 .307 2.990 1.448

251 2 1** .965 1 .546 .002 2 .454 .368 -.326

252 2 2 .700 1 .593 .148 1 .407 .898 .666

253 2 1** .585 1 .614 .298 2 .386 1.229 -.827

254 2 2 .187 1 .711 1.742 1 .289 3.543 1.601

255 2 2 .403 1 .652 .700 1 .348 1.959 1.118

256 2 2 .821 1 .571 .051 1 .429 .622 .507

257 2 2 .324 1 .671 .973 1 .329 2.400 1.268

258 2 2 .939 1 .550 .006 1 .450 .409 .358

259 2 1** .985 1 .537 .000 2 .463 .296 -.263

260 2 2 .166 1 .719 1.915 1 .281 3.789 1.665

261 2 2 .945 1 .530 .005 1 .470 .244 .213

262 2 1** .407 1 .651 .687 2 .349 1.936 -1.110

263 2 1** .240 1 .694 1.381 2 .306 3.021 -1.457

264 2 1** .796 1 .575 .067 2 .425 .675 -.540

265 2 2 .046 1 .783 3.987 1 .217 6.551 2.278

266 2 2 .917 1 .554 .011 1 .446 .445 .386

267 2 2 .501 1 .631 .453 1 .369 1.527 .954

124

268 2 2 .284 1 .682 1.148 1 .318 2.671 1.353

269 2 2 .884 1 .560 .021 1 .440 .502 .427

270 2 2 .224 1 .699 1.476 1 .301 3.159 1.496

271 2 1** .920 1 .526 .010 2 .474 .214 -.181

272 2 1** .594 1 .613 .284 2 .387 1.200 -.814

273 2 2 .951 1 .548 .004 1 .452 .389 .342

274 2 2 .963 1 .533 .002 1 .467 .266 .235

275 2 2 .854 1 .514 .034 1 .486 .143 .097

276 2 2 .836 1 .510 .043 1 .490 .126 .074

277 2 1** .819 1 .571 .052 2 .429 .626 -.510

278 2 1** .359 1 .662 .841 2 .338 2.190 -1.199

279 2 2 .488 1 .634 .482 1 .366 1.580 .976

280 2 2 .599 1 .612 .276 1 .388 1.183 .806

281 2 2 .105 1 .745 2.626 1 .255 4.766 1.902

282 2 2 .057 1 .774 3.636 1 .226 6.099 2.188

283 2 2 .724 1 .588 .125 1 .412 .839 .635

284 2 2 .060 1 .772 3.540 1 .228 5.974 2.163

285 2 1** .666 1 .599 .187 2 .401 .990 -.713

286 2 1** .795 1 .576 .068 2 .424 .677 -.542

287 2 1** .433 1 .646 .615 2 .354 1.815 -1.066

288 2 1** .151 1 .724 2.058 2 .276 3.989 -1.716

289 2 1** .135 1 .731 2.229 2 .269 4.225 -1.774

290 2 1** .792 1 .502 .070 2 .498 .089 -.018

291 2 1** .229 1 .697 1.444 2 .303 3.113 -1.483

292 2 2 .892 1 .521 .018 1 .479 .183 .146

293 2 2 .986 1 .542 .000 1 .458 .337 .299

294 2 2 .209 1 .704 1.578 1 .296 3.308 1.537

295 2 2 .633 1 .605 .228 1 .395 1.081 .758

125

296 2 2 .059 1 .772 3.572 1 .228 6.016 2.171

297 2 1** .819 1 .571 .052 2 .429 .627 -.510

298 2 2 .917 1 .554 .011 1 .446 .445 .386

299 2 2 .501 1 .631 .453 1 .369 1.527 .954

300 2 2 .230 1 .697 1.439 1 .303 3.106 1.481

**. Misclassified case

Classification Resultsa

sex

Predicted Group

Membership

Total 1.00 2.00

Original Count 1.00 90 60 150

2.00 53 97 150

% 1.00 60.0 40.0 100.0

2.00 35.3 64.7 100.0

a. 62.3% of original grouped cases correctly classified.

126

Discriminant analysis by casewise statistic (Researcher would show only from L2 to be sample

which is all analysis together included 10 samples (L1-R5)



Valid 300 100.0

Excluded Missing or out-of-

range group codes

0 .0

At least one missing


0 .0

Both missing or out-of-

range group codes and

at least one missing


0 .0

Total 0 .0

Total 300 100.0

Group Statistics

Sex

Valid N (listwise)

Unweighted Weighted

1 L2 150 150.000

2 L2 150 150.000

Total L2 300 300.000

127

Analysis 1


Eigenvalues

Function Eigenvalue

% of

Variance

Cumulative

%

Canonical

Correlation

1 .009a 100.0 100.0 .094

a. First 1 canonical discriminant functions were used in the

analysis.

Wilks' Lambda

Test of

Function(s)

Wilks'

Lambda Chi-square df Sig.

1 .991 2.645 1 .104

Standardized Canonical

Discriminant Function

Coefficients

Function

1

L2 1.000


discriminant functions Variables ordered by absolute size of correlation within function

Structure Matrix

Function

1

L2 1.000

128

Functions at Group

Centroids

Sex

Function

1

1 -.094

2 .094



Processed 300


range group codes

0

At least one

missing

discriminating

variable

0

Used in Output 300


Sex Prior


Unweighted Weighted

1 .500 150 150.000

2 .500 150 150.000

Total 1.000 300 300.000

129

Casewise Statistics

Cas

e

Nu

mb

er

Actu

al

Grou

p


Discrimin

ant

Scores

Predicte

d Group

P(D>d |

G=g)

P(G

=g |

D=d

)

Square

d

Mahal

anobis

Distan

ce to

Centro

id Group

P(G=g |

D=d)

Squared

Mahalano

bis

Distance

to

Centroid

Function

1

p df

Or

igi

na

l

1 1 1 .936 1 .508 .006 2 .492 .072 -.174

2 1 1 .106 1 .580 2.618 2 .420 3.263 -1.712

3 1 1 .599 1 .529 .277 2 .471 .511 -.620

4 1 1 .111 1 .579 2.540 2 .421 3.176 -1.688

5 1 1 .557 1 .532 .344 2 .468 .601 -.681

6 1 1 .941 1 .508 .005 2 .492 .069 -.168

7 1 1 .274 1 .556 1.195 2 .444 1.642 -1.187

8 1 2** .830 1 .515 .046 1 .485 .162 .308

9 1 2** .826 1 .515 .048 1 .485 .167 .314

10 1 1 .404 1 .544 .695 2 .456 1.045 -.928

11 1 2** .964 1 .507 .002 1 .493 .055 .139

12 1 2** .215 1 .562 1.536 1 .438 2.038 1.334

13 1 1 .958 1 .502 .003 2 .498 .018 -.042

14 1 1 .965 1 .506 .002 2 .494 .054 -.138

15 1 2** .417 1 .543 .658 1 .457 .999 .905

16 1 2** .364 1 .547 .824 1 .453 1.201 1.002

130

17 1 2** .802 1 .516 .063 1 .484 .192 .344

18 1 1 .846 1 .514 .038 2 .486 .147 -.289

19 1 1 .207 1 .564 1.593 2 .436 2.104 -1.356

20 1 2** .598 1 .529 .278 1 .471 .513 .622

21 1 1 .088 1 .584 2.919 2 .416 3.598 -1.803

22 1 1 .374 1 .546 .789 2 .454 1.159 -.982

23 1 2** .358 1 .548 .846 1 .452 1.228 1.014

24 1 2** .623 1 .528 .242 1 .472 .462 .586

25 1 1 .408 1 .543 .685 2 .457 1.033 -.922

26 1 2** .482 1 .537 .494 1 .463 .794 .797

27 1 1 .510 1 .535 .434 2 .465 .718 -.753

28 1 1 .694 1 .523 .155 2 .477 .339 -.488

29 1 1 .865 1 .512 .029 2 .488 .129 -.265

30 1 1 .146 1 .572 2.117 2 .428 2.701 -1.549

31 1 1 .381 1 .546 .768 2 .454 1.133 -.970

32 1 1 .450 1 .540 .571 2 .460 .891 -.850

33 1 1 .689 1 .523 .160 2 .477 .346 -.494

34 1 2** .164 1 .569 1.932 1 .431 2.492 1.484

35 1 1 .633 1 .527 .229 2 .473 .444 -.572

36 1 2** .351 1 .548 .868 1 .452 1.255 1.026

37 1 2** .964 1 .502 .002 1 .498 .020 .049

38 1 2** .724 1 .521 .124 1 .479 .293 .447

39 1 2** .184 1 .567 1.768 1 .433 2.305 1.424

40 1 2** .911 1 .510 .012 1 .490 .090 .206

41 1 2** .105 1 .580 2.622 1 .420 3.268 1.713

42 1 1 .220 1 .562 1.503 2 .438 2.000 -1.320

43 1 1 .841 1 .514 .040 2 .486 .151 -.295

44 1 1 .398 1 .544 .716 2 .456 1.070 -.940

131

45 1 2** .284 1 .555 1.146 1 .445 1.585 1.165

46 1 2** .594 1 .530 .285 1 .470 .521 .628

47 1 1 .641 1 .526 .217 2 .474 .428 -.560

48 1 1 .739 1 .520 .111 2 .480 .272 -.427

49 1 2** .490 1 .537 .477 1 .463 .772 .785

50 1 2** .770 1 .518 .086 1 .482 .231 .387

51 1 2** .926 1 .509 .009 1 .491 .079 .188

52 1 1 .254 1 .558 1.303 2 .442 1.768 -1.236

53 1 2** .449 1 .540 .573 1 .460 .893 .851

54 1 1 .586 1 .530 .296 2 .470 .537 -.639

55 1 2** .509 1 .535 .436 1 .465 .720 .755

56 1 2** .653 1 .526 .202 1 .474 .407 .543

57 1 2** .706 1 .522 .142 1 .478 .320 .471

58 1 2** .490 1 .537 .477 1 .463 .772 .785

59 1 2** .770 1 .518 .086 1 .482 .231 .387

60 1 2** .756 1 .519 .096 1 .481 .249 .405

61 1 1 .578 1 .531 .310 2 .469 .555 -.651

62 1 2** .906 1 .510 .014 1 .490 .094 .212

63 1 1 .241 1 .559 1.373 2 .441 1.850 -1.266

64 1 1 .362 1 .547 .832 2 .453 1.211 -1.006

65 1 1 .776 1 .518 .081 2 .482 .224 -.379

66 1 1 .537 1 .533 .380 2 .467 .648 -.711

67 1 2** .706 1 .522 .142 1 .478 .320 .471

68 1 1 .498 1 .536 .458 2 .464 .749 -.771

69 1 1 .491 1 .537 .475 2 .463 .770 -.783

70 1 2** .993 1 .505 .000 1 .495 .039 .103

71 1 1 .541 1 .533 .373 2 .467 .639 -.705

72 1 1 .624 1 .527 .240 2 .473 .460 -.584

132

73 1 1 .144 1 .573 2.135 2 .427 2.721 -1.555

74 1 1 .502 1 .536 .450 2 .464 .739 -.765

75 1 2** .585 1 .530 .298 1 .470 .539 .640

76 1 2** .561 1 .532 .339 1 .468 .593 .676

77 1 1 .498 1 .536 .458 2 .464 .749 -.771

78 1 1 .946 1 .508 .005 2 .492 .066 -.162

79 1 2** .475 1 .538 .511 1 .462 .815 .809

80 1 2** .139 1 .574 2.192 1 .426 2.785 1.575

81 1 1 .147 1 .572 2.100 2 .428 2.681 -1.543

82 1 1 .291 1 .554 1.117 2 .446 1.551 -1.151

83 1 2** .662 1 .525 .191 1 .475 .391 .531

84 1 1 .313 1 .552 1.018 2 .448 1.433 -1.103

85 1 1 .325 1 .551 .970 2 .449 1.376 -1.079

86 1 2** .521 1 .535 .413 1 .465 .690 .736

87 1 1 .048 1 .596 3.919 2 .404 4.701 -2.074

88 1 1 .251 1 .558 1.317 2 .442 1.785 -1.242

89 1 1 .241 1 .559 1.373 2 .441 1.850 -1.266

90 1 1 .712 1 .522 .137 2 .478 .311 -.464

91 1 1 .865 1 .512 .029 2 .488 .129 -.265

92 1 1 .730 1 .521 .119 2 .479 .285 -.440

93 1 1 .522 1 .535 .411 2 .465 .688 -.735

94 1 1 .667 1 .525 .185 2 .475 .382 -.524

95 1 1 .628 1 .527 .234 2 .473 .452 -.578

96 1 1 .122 1 .577 2.389 2 .423 3.006 -1.640

97 1 1 .757 1 .519 .096 2 .481 .248 -.403

98 1 1 .422 1 .542 .646 2 .458 .984 -.898

99 1 1 .562 1 .532 .337 2 .468 .591 -.675

100 1 1 .174 1 .568 1.846 2 .432 2.393 -1.453

133

101 1 1 .461 1 .539 .544 2 .461 .857 -.832

102 1 1 .089 1 .584 2.898 2 .416 3.575 -1.797

103 1 1 .716 1 .522 .132 2 .478 .305 -.458

104 1 1 .111 1 .579 2.540 2 .421 3.176 -1.688

105 1 1 .134 1 .574 2.242 2 .426 2.841 -1.591

106 1 1 .194 1 .565 1.685 2 .435 2.210 -1.392

107 1 1 .249 1 .558 1.331 2 .442 1.801 -1.248

108 1 2** .585 1 .530 .298 1 .470 .539 .640

109 1 2** .446 1 .540 .582 1 .460 .905 .857

110 1 2** .680 1 .524 .171 1 .476 .362 .507

111 1 2** .087 1 .584 2.923 1 .416 3.603 1.804

112 1 2** .911 1 .510 .012 1 .490 .090 .206

113 1 1 .922 1 .509 .010 2 .491 .082 -.192

114 1 2** .569 1 .531 .325 1 .469 .575 .664

115 1 1 .836 1 .514 .043 2 .486 .156 -.301

116 1 2** .577 1 .531 .311 1 .469 .557 .652

117 1 2** .142 1 .573 2.157 1 .427 2.745 1.563

118 1 2** .812 1 .516 .057 1 .484 .182 .332

119 1 2** .540 1 .533 .375 1 .467 .641 .706

120 1 1 .929 1 .500 .008 2 .500 .010 -.005

121 1 1 .394 1 .544 .726 2 .456 1.082 -.946

122 1 1 .934 1 .501 .007 2 .499 .011 -.011

123 1 1 .869 1 .512 .027 2 .488 .124 -.259

124 1 1 .487 1 .537 .483 2 .463 .781 -.789

125 1 2** .557 1 .532 .346 1 .468 .603 .682

126 1 1 .429 1 .542 .627 2 .458 .960 -.886

127 1 1 .951 1 .507 .004 2 .493 .063 -.156

128 1 2** .733 1 .520 .116 1 .480 .280 .435

134

129 1 1 .970 1 .506 .001 2 .494 .051 -.132

130 1 2** .274 1 .556 1.198 1 .444 1.646 1.189

131 1 2** .577 1 .531 .311 1 .469 .557 .652

132 1 2** .142 1 .573 2.157 1 .427 2.745 1.563

133 1 2** .812 1 .516 .057 1 .484 .182 .332

134 1 1 .603 1 .529 .271 2 .471 .502 -.614

135 1 2** .793 1 .517 .069 1 .483 .203 .357

136 1 2** .295 1 .554 1.095 1 .446 1.525 1.141

137 1 2** .505 1 .536 .444 1 .464 .731 .761

138 1 2** .213 1 .563 1.551 1 .437 2.056 1.340

139 1 2** .475 1 .538 .511 1 .462 .815 .809

140 1 2** .585 1 .530 .298 1 .470 .539 .640

141 1 2** .446 1 .540 .582 1 .460 .905 .857

142 1 2** .680 1 .524 .171 1 .476 .362 .507

143 1 2** .577 1 .531 .311 1 .469 .557 .652

144 1 2** .142 1 .573 2.157 1 .427 2.745 1.563

145 1 2** .812 1 .516 .057 1 .484 .182 .332

146 1 2** .577 1 .531 .311 1 .469 .557 .652

147 1 2** .142 1 .573 2.157 1 .427 2.745 1.563

148 1 2** .812 1 .516 .057 1 .484 .182 .332

149 1 1 .291 1 .554 1.117 2 .446 1.551 -1.151

150 1 2** .417 1 .543 .658 1 .457 .999 .905

151 2 2 .585 1 .530 .298 1 .470 .539 .640

152 2 2 .446 1 .540 .582 1 .460 .905 .857

153 2 2 .680 1 .524 .171 1 .476 .362 .507

154 2 2 .087 1 .584 2.923 1 .416 3.603 1.804

155 2 2 .911 1 .510 .012 1 .490 .090 .206

156 2 1** .922 1 .509 .010 2 .491 .082 -.192

135

157 2 2 .428 1 .542 .629 1 .458 .963 .887

158 2 2 .830 1 .515 .046 1 .485 .162 .308

159 2 2 .671 1 .524 .181 1 .476 .376 .519

160 2 1** .953 1 .502 .003 2 .498 .017 -.035

161 2 2 .585 1 .530 .298 1 .470 .539 .640

162 2 2 .497 1 .536 .460 1 .464 .751 .773

163 2 2 .163 1 .570 1.949 1 .430 2.511 1.490

164 2 2 .548 1 .533 .360 1 .467 .622 .694

165 2 2 .339 1 .549 .914 1 .451 1.309 1.050

166 2 2 .733 1 .520 .116 1 .480 .280 .435

167 2 2 .287 1 .554 1.133 1 .446 1.570 1.159

168 2 1** .331 1 .550 .946 2 .450 1.348 -1.067

169 2 2 .532 1 .534 .390 1 .466 .660 .718

170 2 2 .456 1 .539 .555 1 .461 .871 .839

171 2 2 .164 1 .569 1.932 1 .431 2.492 1.484

172 2 2 .756 1 .519 .096 1 .481 .249 .405

173 2 1** .939 1 .501 .006 2 .499 .012 -.017

174 2 1** .220 1 .562 1.503 2 .438 2.000 -1.320

175 2 2 .274 1 .556 1.198 1 .444 1.646 1.189

176 2 2 .849 1 .513 .036 1 .487 .143 .284

177 2 2 .339 1 .549 .914 1 .451 1.309 1.050

178 2 2 .209 1 .563 1.581 1 .437 2.090 1.352

179 2 2 .126 1 .576 2.337 1 .424 2.949 1.623

180 2 2 .400 1 .544 .708 1 .456 1.060 .935

181 2 2 .816 1 .515 .054 1 .485 .177 .326

182 2 2 .410 1 .543 .678 1 .457 1.023 .917

183 2 2 .227 1 .561 1.462 1 .439 1.953 1.303

184 2 2 .120 1 .577 2.412 1 .423 3.032 1.647

136

185 2 2 .108 1 .579 2.583 1 .421 3.224 1.701

186 2 2 .227 1 .561 1.462 1 .439 1.953 1.303

187 2 2 .030 1 .605 4.727 1 .395 5.581 2.268

188 2 1** .941 1 .508 .005 2 .492 .069 -.168

189 2 1** .220 1 .562 1.503 2 .438 2.000 -1.320

190 2 2 .180 1 .567 1.801 1 .433 2.342 1.436

191 2 2 .027 1 .607 4.886 1 .393 5.754 2.305

192 2 2 .161 1 .570 1.966 1 .430 2.530 1.496

193 2 2 .517 1 .535 .420 1 .465 .700 .743

194 2 2 .070 1 .589 3.284 1 .411 4.003 1.906

195 2 2 .258 1 .557 1.279 1 .443 1.740 1.225

196 2 2 .521 1 .535 .413 1 .465 .690 .736

197 2 1** .048 1 .596 3.919 2 .404 4.701 -2.074

198 2 1** .251 1 .558 1.317 2 .442 1.785 -1.242

199 2 1** .241 1 .559 1.373 2 .441 1.850 -1.266

200 2 1** .712 1 .522 .137 2 .478 .311 -.464

201 2 1** .865 1 .512 .029 2 .488 .129 -.265

202 2 1** .730 1 .521 .119 2 .479 .285 -.440

203 2 1** .522 1 .535 .411 2 .465 .688 -.735

204 2 1** .667 1 .525 .185 2 .475 .382 -.524

205 2 1** .628 1 .527 .234 2 .473 .452 -.578

206 2 1** .122 1 .577 2.389 2 .423 3.006 -1.640

207 2 1** .757 1 .519 .096 2 .481 .248 -.403

208 2 1** .422 1 .542 .646 2 .458 .984 -.898

209 2 1** .562 1 .532 .337 2 .468 .591 -.675

210 2 1** .174 1 .568 1.846 2 .432 2.393 -1.453

211 2 1** .461 1 .539 .544 2 .461 .857 -.832

212 2 1** .089 1 .584 2.898 2 .416 3.575 -1.797

137

213 2 1** .716 1 .522 .132 2 .478 .305 -.458

214 2 1** .111 1 .579 2.540 2 .421 3.176 -1.688

215 2 1** .134 1 .574 2.242 2 .426 2.841 -1.591

216 2 1** .194 1 .565 1.685 2 .435 2.210 -1.392

217 2 1** .249 1 .558 1.331 2 .442 1.801 -1.248

218 2 2 .486 1 .537 .485 1 .463 .783 .791

219 2 2 .227 1 .561 1.462 1 .439 1.953 1.303

220 2 2 .610 1 .528 .260 1 .472 .487 .604

221 2 2 .602 1 .529 .272 1 .471 .504 .616

222 2 1** .461 1 .539 .544 2 .461 .857 -.832

223 2 2 .253 1 .558 1.306 1 .442 1.772 1.237

224 2 2 .387 1 .545 .749 1 .455 1.111 .960

225 2 2 .310 1 .552 1.033 1 .448 1.451 1.110

226 2 2 .467 1 .539 .528 1 .461 .837 .821

227 2 2 .081 1 .586 3.048 1 .414 3.742 1.840

228 2 2 .072 1 .588 3.241 1 .412 3.955 1.894

229 2 2 .671 1 .524 .181 1 .476 .376 .519

230 2 1** .855 1 .513 .033 2 .487 .138 -.277

231 2 1** .368 1 .547 .810 2 .453 1.185 -.994

232 2 1** .346 1 .549 .888 2 .451 1.279 -1.037

233 2 2 .224 1 .561 1.477 1 .439 1.970 1.309

234 2 2 .393 1 .545 .728 1 .455 1.085 .948

235 2 2 .706 1 .522 .142 1 .478 .320 .471

236 2 1** .510 1 .535 .434 2 .465 .718 -.753

237 2 2 .636 1 .527 .224 1 .473 .438 .568

238 2 2 .220 1 .562 1.506 1 .438 2.004 1.321

239 2 1** .104 1 .580 2.637 2 .420 3.284 -1.718

240 2 1** .196 1 .565 1.670 2 .435 2.192 -1.386

138

241 2 2 .355 1 .548 .857 1 .452 1.241 1.020

242 2 1** .574 1 .531 .316 2 .469 .564 -.657

243 2 1** .590 1 .530 .290 2 .470 .528 -.633

244 2 2 .671 1 .524 .181 1 .476 .376 .519

245 2 1** .827 1 .515 .048 2 .485 .166 -.313

246 2 1** .917 1 .509 .011 2 .491 .086 -.198

247 2 1** .266 1 .557 1.235 2 .443 1.689 -1.205

248 2 1** .780 1 .518 .078 2 .482 .218 -.373

249 2 2 .868 1 .512 .028 1 .488 .125 .260

250 2 1** .624 1 .527 .240 2 .473 .460 -.584

251 2 1** .443 1 .540 .589 2 .460 .914 -.862

252 2 1** .994 1 .505 .000 2 .495 .038 -.102

253 2 1** .865 1 .512 .029 2 .488 .129 -.265

254 2 1** .582 1 .530 .303 2 .470 .546 -.645

255 2 2 .935 1 .501 .007 1 .499 .011 .013

256 2 1** .654 1 .526 .201 2 .474 .405 -.542

257 2 1** .803 1 .516 .062 2 .484 .191 -.343

258 2 1** .322 1 .551 .981 2 .449 1.390 -1.085

259 2 1** .391 1 .545 .736 2 .455 1.095 -.952

260 2 1** .254 1 .558 1.303 2 .442 1.768 -1.236

261 2 1** .676 1 .524 .175 2 .476 .367 -.512

262 2 1** .006 1 .631 7.572 2 .369 8.644 -2.846

263 2 1** .070 1 .589 3.279 2 .411 3.997 -1.905

264 2 1** .545 1 .533 .366 2 .467 .629 -.699

265 2 1** .272 1 .556 1.208 2 .444 1.658 -1.193

266 2 2 .315 1 .552 1.008 1 .448 1.422 1.098

267 2 2 .102 1 .581 2.681 1 .419 3.333 1.732

268 2 2 .367 1 .547 .813 1 .453 1.188 .996

139

269 2 2 .065 1 .590 3.395 1 .410 4.124 1.937

270 2 2 .156 1 .571 2.017 1 .429 2.588 1.514

271 2 2 .826 1 .515 .048 1 .485 .167 .314

272 2 2 .826 1 .515 .048 1 .485 .167 .314

273 2 1** .404 1 .544 .695 2 .456 1.045 -.928

274 2 2 .964 1 .507 .002 1 .493 .055 .139

275 2 2 .215 1 .562 1.536 1 .438 2.038 1.334

276 2 1** .958 1 .502 .003 2 .498 .018 -.042

277 2 1** .965 1 .506 .002 2 .494 .054 -.138

278 2 1** .865 1 .512 .029 2 .488 .129 -.265

279 2 1** .146 1 .572 2.117 2 .428 2.701 -1.549

280 2 1** .381 1 .546 .768 2 .454 1.133 -.970

281 2 1** .450 1 .540 .571 2 .460 .891 -.850

282 2 1** .689 1 .523 .160 2 .477 .346 -.494

283 2 2 .706 1 .522 .142 1 .478 .320 .471

284 2 1** .498 1 .536 .458 2 .464 .749 -.771

285 2 1** .491 1 .537 .475 2 .463 .770 -.783

286 2 2 .993 1 .505 .000 1 .495 .039 .103

287 2 1** .541 1 .533 .373 2 .467 .639 -.705

288 2 1** .936 1 .508 .006 2 .492 .072 -.174

289 2 1** .106 1 .580 2.618 2 .420 3.263 -1.712

290 2 1** .599 1 .529 .277 2 .471 .511 -.620

291 2 1** .111 1 .579 2.540 2 .421 3.176 -1.688

292 2 1** .557 1 .532 .344 2 .468 .601 -.681

293 2 1** .953 1 .502 .003 2 .498 .017 -.035

294 2 2 .585 1 .530 .298 1 .470 .539 .640

295 2 2 .497 1 .536 .460 1 .464 .751 .773

296 2 2 .163 1 .570 1.949 1 .430 2.511 1.490

140

297 2 2 .548 1 .533 .360 1 .467 .622 .694

298 2 2 .315 1 .552 1.008 1 .448 1.422 1.098

299 2 2 .102 1 .581 2.681 1 .419 3.333 1.732

300 2 2 .486 1 .537 .485 1 .463 .783 .791


Sexual determination from phalange’s length.

One-Sample statistic

female male

Mean Std.

Deviation Mean

Std.

Deviation

L1 62.1101 4.85163 64.4235 4.95630

L2 87.4559 5.33152 90.1099 5.78386

L3 94.5451 5.53570 99.1415 4.03577

L4 87.8580 6.55835 90.7459 6.08709

L5 68.6751 5.74333 71.3041 6.10807

R1 62.6071 5.15817 64.9470 4.52436

R2 87.5296 5.47939 90.4294 5.46892

R3 95.2107 5.52225 99.3863 4.39824

R4 88.5542 5.66079 91.0730 6.16285

R5 70.5467 6.16850 70.9357 7.61248

141

Casewise : Prediction of sexual determination from proximal inter-phalangeal joint’s width.



Valid 300 100.0

Excluded Missing or out-of-range group codes 0 .0

At least one missing discriminating variable 0 .0

Both missing or out-of-range group codes and at least

one missing discriminating variable

0 .0

Total 0 .0

Total 300 100.0

Group Statistics

sex

Valid N (listwise)

Unweighted Weighted

1.00 R5 150 150.000

L1 150 150.000

L2 150 150.000

L3 150 150.000

L4 150 150.000

142

L5 150 150.000

R1 150 150.000

R2 150 150.000

R3 150 150.000

R4 150 150.000

2.00 R5 150 150.000

L1 150 150.000

L2 150 150.000

L3 150 150.000

L4 150 150.000

L5 150 150.000

R1 150 150.000

R2 150 150.000

R3 150 150.000

R4 150 150.000

Total R5 300 300.000

L1 300 300.000

L2 300 300.000

L3 300 300.000

L4 300 300.000

L5 300 300.000

R1 300 300.000

R2 300 300.000

R3 300 300.000

R4 300 300.000

143

Analysis 1


Eigenvalues

Function Eigenvalue

% of

Variance

Cumulative

%

Canonical

Correlation

1 .402a 100.0 100.0 .535

a. First 1 canonical discriminant functions were used in the analysis.

Wilks' Lambda

Test of

Function(s) Wilks' Lambda

Chi-

square df Sig.

1 .713 98.923 10 .000

Standardized Canonical Discriminant Function Coefficients

Function

1

R5 -.404

L1 .055

L2 -.416

L3 1.256

L4 -.681

L5 .479

R1 .100

R2 -.170

R3 .590

R4 -.204

144

Structure Matrix

Function

1

L3 .751

R3 .662

R2 .419

R1 .382

L2 .378

L1 .373

L4 .361

L5 .351

R4 .337

R5 .044


discriminant functions

Variables ordered by absolute size of correlation within function.

Functions at Group Centroids

sex

Function

1

1.00 -.632

2.00 .632

Unstandardized canonical discriminant functions evaluated at group means

145



Processed 300


range group codes

0

At least one missing

discriminating

variable

0

Used in Output 300


sex Prior


Unweighted Weighted

1.00 .500 150 150.000

2.00 .500 150 150.000

Total 1.000 300 300.000

146

Casewise Statistics

Case

Nu

mbe

r

Actual

Group


Discrimina

nt Scores

Predi

cted

Grou

p

P(D>d |

G=g)

P(G

=g |

D=d

)

Square

d

Mahala

nobis

Distanc

e to

Centroi

d

Grou

p

P(G=

g |

D=d)

Squared

Mahalanob

is Distance

to

Centroid Function 1

p df

Or

igi

na

l

1 1 1 .448 1 .853 .575 2 .147 4.086 -1.390

2 1 1 .313 1 .888 1.017 2 .112 5.161 -1.640

3 1 1 .047 1 .965 3.936 2 .035 10.545 -2.616

4 1 2** .845 1 .634 .038 1 .366 1.139 .436

5 1 1 .270 1 .899 1.216 2 .101 5.597 -1.734

6 1 1 .202 1 .918 1.627 2 .082 6.445 -1.907

7 1 1 .646 1 .554 .210 2 .446 .647 -.173

8 1 1 .472 1 .847 .518 2 .153 3.933 -1.352

9 1 2** .646 1 .554 .211 1 .446 .647 .173

10 1 2** .633 1 .802 .229 1 .198 3.033 1.110

11 1 1 .648 1 .798 .209 2 .202 2.959 -1.088

12 1 1 .552 1 .512 .353 2 .488 .448 -.038

13 1 2** .803 1 .619 .062 1 .381 1.029 .383

14 1 2** .536 1 .504 .383 1 .496 .415 .013

15 1 1 .191 1 .920 1.707 2 .080 6.605 -1.938

16 1 2** .667 1 .563 .186 1 .437 .693 .201

17 1 1 .461 1 .849 .544 2 .151 4.004 -1.369

147

18 1 1 .743 1 .771 .108 2 .229 2.533 -.960

19 1 2** .580 1 .817 .306 1 .183 3.300 1.185

20 1 1 .159 1 .929 1.982 2 .071 7.135 -2.039

21 1 1 .965 1 .677 .002 2 .323 1.486 -.587

22 1 1 .658 1 .795 .196 2 .205 2.912 -1.075

23 1 1 .960 1 .676 .003 2 .324 1.470 -.581

24 1 1 .560 1 .515 .340 2 .485 .462 -.048

25 1 2** .675 1 .791 .176 1 .209 2.833 1.052

26 1 1 .895 1 .653 .017 2 .347 1.280 -.500

27 1 1 .535 1 .503 .385 2 .497 .413 -.011

28 1 1 .548 1 .510 .360 2 .490 .440 -.032

29 1 1 .564 1 .517 .334 2 .483 .470 -.054

30 1 1 .419 1 .861 .654 2 .139 4.293 -1.440

31 1 1 .950 1 .672 .004 2 .328 1.442 -.569

32 1 1 .566 1 .518 .330 2 .482 .475 -.057

33 1 1 .880 1 .729 .023 2 .271 2.002 -.783

34 1 1 .928 1 .665 .008 2 .335 1.376 -.541

35 1 2** .480 1 .844 .498 1 .156 3.878 1.338

36 1 1 .191 1 .921 1.711 2 .079 6.611 -1.940

37 1 1 .063 1 .959 3.444 2 .041 9.728 -2.487

38 1 1 .521 1 .833 .412 2 .167 3.630 -1.274

39 1 2** .843 1 .741 .039 1 .259 2.137 .830

40 1 1 .311 1 .889 1.027 2 .111 5.183 -1.645

41 1 1 .890 1 .651 .019 2 .349 1.265 -.493

42 1 2** .632 1 .548 .230 1 .452 .614 .152

43 1 1 .469 1 .847 .523 2 .153 3.947 -1.355

44 1 2** .839 1 .632 .041 1 .368 1.123 .428

45 1 1 .766 1 .604 .089 2 .396 .932 -.334

148

46 1 1 .710 1 .581 .138 2 .419 .796 -.260

47 1 1 .563 1 .517 .335 2 .483 .468 -.053

48 1 1 .709 1 .581 .139 2 .419 .793 -.259

49 1 1 .735 1 .592 .114 2 .408 .856 -.293

50 1 1 .993 1 .687 .000 2 .313 1.572 -.622

51 1 1 .062 1 .959 3.482 2 .041 9.793 -2.498

52 1 2** .696 1 .576 .153 1 .424 .762 .241

53 1 1 .655 1 .796 .199 2 .204 2.923 -1.078

54 1 1 .379 1 .871 .773 2 .129 4.590 -1.511

55 1 1 .587 1 .815 .294 2 .185 3.261 -1.174

56 1 1 .108 1 .944 2.588 2 .056 8.249 -2.240

57 1 1 .474 1 .846 .512 2 .154 3.915 -1.347

58 1 1 .599 1 .812 .276 2 .188 3.200 -1.157

59 1 1 .795 1 .755 .068 2 .245 2.321 -.892

60 1 2** .733 1 .591 .117 1 .409 .850 .290

61 1 1 .464 1 .849 .536 2 .151 3.982 -1.364

62 1 1 .364 1 .875 .823 2 .125 4.711 -1.539

63 1 1 .772 1 .762 .084 2 .238 2.411 -.921

64 1 1 .803 1 .753 .062 2 .247 2.289 -.881

65 1 2** .728 1 .589 .121 1 .411 .839 .284

66 1 1 .712 1 .582 .136 2 .418 .800 -.263

67 1 1 .981 1 .683 .001 2 .317 1.536 -.608

68 1 1 .723 1 .776 .125 2 .224 2.615 -.985

69 1 1 .045 1 .965 4.021 2 .035 10.683 -2.637

70 1 1 .163 1 .928 1.942 2 .072 7.058 -2.025

71 1 2** .288 1 .895 1.128 1 .105 5.408 1.694

72 1 1 .029 1 .972 4.797 2 .028 11.927 -2.822

73 1 1 .995 1 .688 .000 2 .312 1.580 -.626

149

74 1 1 .849 1 .636 .036 2 .364 1.152 -.442

75 1 2** .635 1 .550 .225 1 .450 .623 .158

76 1 1 .020 1 .977 5.419 2 .023 12.895 -2.959

77 1 2** .801 1 .618 .063 1 .382 1.023 .380

78 1 1 .975 1 .698 .001 2 .302 1.677 -.664

79 1 1 .031 1 .971 4.668 2 .029 11.722 -2.792

80 1 1 .749 1 .597 .102 2 .403 .890 -.312

81 1 1 .000 1 .996 14.132 2 .004 25.226 -4.391

82 1 1 .998 1 .690 .000 2 .310 1.602 -.634

83 1 1 .037 1 .969 4.373 2 .031 11.252 -2.723

84 1 2** .604 1 .536 .268 1 .464 .555 .114

85 1 1 .915 1 .718 .011 2 .282 1.877 -.738

86 1 1 .191 1 .921 1.714 2 .079 6.617 -1.941

87 1 1 .437 1 .856 .604 2 .144 4.163 -1.409

88 1 1 .889 1 .650 .020 2 .350 1.261 -.491

89 1 1 .329 1 .884 .954 2 .116 5.017 -1.608

90 1 1 .007 1 .985 7.330 2 .015 15.765 -3.339

91 1 2** .572 1 .819 .320 1 .181 3.345 1.197

92 1 1 .590 1 .529 .290 2 .471 .526 -.093

93 1 2** .799 1 .617 .065 1 .383 1.018 .377

94 1 2** .319 1 .887 .993 1 .113 5.106 1.628

95 1 2** .998 1 .690 .000 1 .310 1.603 .634

96 1 1 .560 1 .515 .340 2 .485 .462 -.048

97 1 1 .775 1 .761 .081 2 .239 2.398 -.917

98 1 2** .955 1 .674 .003 1 .326 1.457 .575

99 1 2** .864 1 .641 .029 1 .359 1.191 .460

100 1 1 .587 1 .528 .296 2 .472 .518 -.088

101 1 1 .575 1 .818 .314 2 .182 3.326 -1.192

150

102 1 2** .619 1 .806 .247 1 .194 3.099 1.129

103 1 1 .871 1 .644 .026 2 .356 1.211 -.469

104 1 2** .689 1 .573 .160 1 .427 .745 .232

105 1 1 .709 1 .581 .139 2 .419 .792 -.259

106 1 1 .291 1 .894 1.117 2 .106 5.382 -1.688

107 1 1 .411 1 .863 .677 2 .137 4.350 -1.454

108 1 1 .876 1 .646 .024 2 .354 1.226 -.476

109 1 1 .810 1 .621 .058 2 .379 1.046 -.391

110 1 2** .677 1 .568 .173 1 .432 .717 .215

111 1 1 .544 1 .508 .368 2 .492 .431 -.025

112 1 1 .615 1 .541 .253 2 .459 .579 -.129

113 1 1 .446 1 .853 .580 2 .147 4.101 -1.393

114 1 2** .645 1 .554 .212 1 .446 .644 .171

115 1 1 .370 1 .873 .803 2 .127 4.662 -1.527

116 1 2** .590 1 .529 .290 1 .471 .526 .093

117 1 2** .877 1 .646 .024 1 .354 1.228 .476

118 1 2** .672 1 .566 .179 1 .434 .706 .209

119 1 2** .560 1 .822 .339 1 .178 3.405 1.214

120 1 2** .595 1 .531 .283 1 .469 .535 .100

121 1 1 .887 1 .650 .020 2 .350 1.258 -.490

122 1 2** .804 1 .752 .061 1 .248 2.283 .879

123 1 1 .914 1 .660 .012 2 .340 1.336 -.524

124 1 1 .720 1 .585 .129 2 .415 .818 -.273

125 1 2** .601 1 .534 .273 1 .466 .549 .109

126 1 2** .932 1 .712 .007 1 .288 1.818 .717

127 1 1 .844 1 .740 .038 2 .260 2.130 -.828

128 1 1 .615 1 .807 .253 2 .193 3.121 -1.135

129 1 1 .710 1 .581 .139 2 .419 .794 -.259

151

130 1 1 .704 1 .579 .145 2 .421 .780 -.251

131 1 2** .648 1 .555 .208 1 .445 .651 .175

132 1 2** .591 1 .530 .288 1 .470 .527 .095

133 1 1 .544 1 .508 .368 2 .492 .431 -.025

134 1 1 .030 1 .972 4.725 2 .028 11.812 -2.805

135 1 2** .953 1 .674 .003 1 .326 1.452 .573

136 1 2** .745 1 .770 .106 1 .230 2.525 .957

137 1 1 .003 1 .990 9.004 2 .010 18.181 -3.632

138 1 1 .682 1 .788 .168 2 .212 2.799 -1.041

139 1 1 .587 1 .815 .295 2 .185 3.262 -1.175

140 1 1 .881 1 .648 .022 2 .352 1.241 -.482

141 1 1 .362 1 .875 .832 2 .125 4.732 -1.544

142 1 1 .931 1 .665 .008 2 .335 1.383 -.544

143 1 1 .047 1 .965 3.936 2 .035 10.545 -2.616

144 1 1 .737 1 .772 .113 2 .228 2.557 -.967

145 1 1 .309 1 .889 1.036 2 .111 5.203 -1.649

146 1 1 .728 1 .775 .121 2 .225 2.596 -.980

147 1 2** .564 1 .822 .334 1 .178 3.389 1.209

148 1 2** .590 1 .529 .290 1 .471 .526 .093

149 1 1 .646 1 .554 .211 2 .446 .647 -.173

150 1 1 .994 1 .687 .000 2 .313 1.577 -.624

151 2 2 .590 1 .529 .290 1 .471 .526 .093

152 2 2 .877 1 .646 .024 1 .354 1.228 .476

153 2 2 .672 1 .566 .179 1 .434 .706 .209

154 2 2 .560 1 .822 .339 1 .178 3.405 1.214

155 2 2 .595 1 .531 .283 1 .469 .535 .100

156 2 2 .933 1 .666 .007 1 .334 1.389 .547

157 2 2 .739 1 .593 .111 1 .407 .864 .298

152

158 2 2 .686 1 .787 .163 1 .213 2.779 1.035

159 2 2 .553 1 .824 .352 1 .176 3.446 1.225

160 2 2 .690 1 .786 .159 1 .214 2.763 1.031

161 2 1** .577 1 .523 .311 2 .477 .497 -.074

162 2 2 .519 1 .834 .415 1 .166 3.639 1.276

163 2 2 .002 1 .992 10.051 1 .008 19.656 3.802

164 2 2 .295 1 .893 1.097 1 .107 5.339 1.679

165 2 2 .766 1 .604 .089 1 .396 .932 .334

166 2 2 .804 1 .752 .061 1 .248 2.283 .879

167 2 1** .590 1 .529 .290 2 .471 .525 -.093

168 2 1** .753 1 .768 .099 2 .232 2.491 -.947

169 2 2 .002 1 .991 9.325 1 .009 18.636 3.685

170 2 2 .653 1 .797 .202 1 .203 2.932 1.081

171 2 2 .895 1 .724 .017 1 .276 1.947 .764

172 2 2 .854 1 .737 .034 1 .263 2.094 .815

173 2 2 .529 1 .831 .396 1 .169 3.580 1.261

174 2 2 .109 1 .944 2.564 1 .056 8.205 2.233

175 2 2 .531 1 .502 .392 1 .498 .406 .005

176 2 2 .852 1 .738 .035 1 .262 2.104 .819

177 2 2 .593 1 .813 .285 1 .187 3.231 1.166

178 2 2 .976 1 .698 .001 1 .302 1.674 .662

179 2 2 .404 1 .864 .697 1 .136 4.402 1.466

180 2 2 .354 1 .878 .860 1 .122 4.799 1.559

181 2 2 .655 1 .558 .199 1 .442 .667 .185

182 2 2 .622 1 .544 .243 1 .456 .593 .138

183 2 1** .564 1 .517 .333 2 .483 .471 -.055

184 2 2 .947 1 .671 .004 1 .329 1.431 .565

185 2 2 .601 1 .534 .274 1 .466 .548 .108

153

186 2 2 .805 1 .619 .061 1 .381 1.033 .385

187 2 2 .704 1 .579 .144 1 .421 .780 .252

188 2 2 .638 1 .551 .222 1 .449 .628 .161

189 2 2 .839 1 .632 .041 1 .368 1.123 .428

190 2 2 .868 1 .733 .028 1 .267 2.043 .798

191 2 2 .018 1 .978 5.577 1 .022 13.140 2.993

192 2 2 .582 1 .525 .304 1 .475 .507 .081

193 2 2 .036 1 .969 4.405 1 .031 11.303 2.730

194 2 1** .604 1 .535 .270 2 .465 .553 -.112

195 2 1** .753 1 .599 .099 2 .401 .899 -.316

196 2 2 .623 1 .544 .242 1 .456 .595 .139

197 2 2 .763 1 .765 .091 1 .235 2.449 .933

198 2 1** .560 1 .515 .340 2 .485 .462 -.048

199 2 2 .793 1 .614 .069 1 .386 1.001 .369

200 2 2 .955 1 .674 .003 1 .326 1.457 .575

201 2 2 .864 1 .641 .029 1 .359 1.191 .460

202 2 2 .344 1 .880 .897 1 .120 4.885 1.579

203 2 1** .575 1 .818 .314 2 .182 3.325 -1.192

204 2 2 .897 1 .724 .017 1 .276 1.941 .762

205 2 2 .692 1 .785 .157 1 .215 2.752 1.027

206 2 2 .451 1 .852 .567 1 .148 4.065 1.385

207 2 2 .693 1 .574 .156 1 .426 .754 .237

208 2 2 .357 1 .877 .847 1 .123 4.767 1.552

209 2 2 .450 1 .852 .570 1 .148 4.074 1.387

210 2 2 .687 1 .787 .162 1 .213 2.776 1.035

211 2 2 .696 1 .576 .152 1 .424 .762 .241

212 2 2 .677 1 .568 .173 1 .432 .717 .215

213 2 1** .544 1 .508 .368 2 .492 .431 -.025

154

214 2 2 .816 1 .749 .054 1 .251 2.239 .865

215 2 2 .781 1 .610 .077 1 .390 .970 .353

216 2 2 .645 1 .554 .212 1 .446 .644 .171

217 2 2 .616 1 .541 .252 1 .459 .580 .130

218 2 2 .661 1 .561 .193 1 .439 .680 .193

219 2 1** .776 1 .608 .081 2 .392 .959 -.348

220 2 1** .839 1 .632 .041 2 .368 1.123 -.428

221 2 2 .650 1 .798 .206 1 .202 2.948 1.085

222 2 2 .174 1 .925 1.844 1 .075 6.870 1.990

223 2 2 .792 1 .614 .070 1 .386 .998 .367

224 2 2 .722 1 .586 .126 1 .414 .824 .276

225 2 2 .758 1 .601 .095 1 .399 .912 .324

226 2 2 .915 1 .660 .011 1 .340 1.339 .525

227 2 2 .802 1 .753 .063 1 .247 2.291 .882

228 2 2 .045 1 .965 4.015 1 .035 10.674 2.635

229 2 2 .659 1 .795 .195 1 .205 2.907 1.073

230 2 2 .677 1 .790 .173 1 .210 2.821 1.048

231 2 1** .574 1 .819 .316 2 .181 3.333 -1.194

232 2 2 .613 1 .808 .255 1 .192 3.128 1.137

233 2 2 .582 1 .817 .303 1 .183 3.291 1.182

234 2 2 .945 1 .708 .005 1 .292 1.776 .701

235 2 1** .866 1 .733 .028 2 .267 2.050 -.800

236 2 1** .704 1 .579 .145 2 .421 .779 -.251

237 2 1** .809 1 .621 .059 2 .379 1.043 -.389

238 2 1** .635 1 .550 .225 2 .450 .623 -.157

239 2 2 .417 1 .861 .658 1 .139 4.303 1.443

240 2 2 .032 1 .971 4.583 1 .029 11.587 2.772

241 2 2 .848 1 .636 .037 1 .364 1.149 .440

155

242 2 2 .667 1 .563 .185 1 .437 .693 .201

243 2 2 .569 1 .820 .325 1 .180 3.361 1.202

244 2 2 .650 1 .556 .206 1 .444 .655 .178

245 2 2 .605 1 .536 .267 1 .464 .557 .114

246 2 2 .710 1 .581 .138 1 .419 .795 .260

247 2 2 .397 1 .866 .716 1 .134 4.451 1.478

248 2 2 .894 1 .724 .018 1 .276 1.949 .764

249 2 2 .878 1 .646 .024 1 .354 1.231 .478

250 2 1** .559 1 .515 .341 2 .485 .462 -.048

251 2 2 .366 1 .874 .816 1 .126 4.695 1.535

252 2 2 .906 1 .721 .014 1 .279 1.909 .750

253 2 2 .489 1 .842 .479 1 .158 3.823 1.324

254 2 1** .755 1 .600 .097 2 .400 .906 -.320

255 2 2 .326 1 .885 .965 1 .115 5.043 1.614

256 2 2 .188 1 .921 1.736 1 .079 6.661 1.949

257 2 2 .619 1 .806 .247 1 .194 3.100 1.129

258 2 1** .760 1 .602 .093 2 .398 .917 -.326

259 2 2 .654 1 .558 .201 1 .442 .665 .184

260 2 1** .949 1 .672 .004 2 .328 1.439 -.568

261 2 2 .635 1 .550 .225 1 .450 .623 .158

262 2 2 .902 1 .655 .015 1 .345 1.300 .509

263 2 1** .682 1 .788 .167 2 .212 2.797 -1.041

264 2 2 .877 1 .646 .024 1 .354 1.228 .477

265 2 2 .244 1 .906 1.359 1 .094 5.899 1.797

266 2 2 .955 1 .674 .003 1 .326 1.455 .575

267 2 2 .845 1 .740 .038 1 .260 2.127 .827

268 2 1** .617 1 .541 .250 2 .459 .582 -.132

269 2 2 .534 1 .503 .387 1 .497 .411 .009

156

270 2 2 .712 1 .780 .136 1 .220 2.664 1.000

271 2 2 .634 1 .549 .226 1 .451 .620 .156

272 2 2 .781 1 .610 .078 1 .390 .970 .353

273 2 2 .989 1 .686 .000 1 .314 1.561 .618

274 2 1** .552 1 .512 .353 2 .488 .448 -.038

275 2 2 .803 1 .619 .062 1 .381 1.029 .383

276 2 2 .536 1 .504 .383 1 .496 .415 .013

277 2 2 .982 1 .696 .001 1 .304 1.654 .655

278 2 2 .617 1 .807 .250 1 .193 3.108 1.131

279 2 2 .870 1 .644 .027 1 .356 1.209 .468

280 2 1** .566 1 .518 .330 2 .482 .475 -.057

281 2 1** .880 1 .729 .023 2 .271 2.002 -.783

282 2 2 .521 1 .833 .412 1 .167 3.630 1.274

283 2 2 .635 1 .550 .225 1 .450 .623 .158

284 2 2 .086 1 .951 2.955 1 .049 8.894 2.351

285 2 1** .611 1 .539 .259 2 .461 .569 -.123

286 2 2 .830 1 .745 .046 1 .255 2.185 .847

287 2 2 .717 1 .584 .132 1 .416 .811 .269

288 2 1** .448 1 .853 .575 2 .147 4.086 -1.390

289 2 1** .826 1 .627 .048 2 .373 1.089 -.412

290 2 2 .835 1 .743 .044 1 .257 2.167 .840

291 2 2 .461 1 .849 .542 1 .151 3.999 1.368

292 2 2 .158 1 .930 1.995 1 .070 7.159 2.044

293 2 2 .627 1 .804 .236 1 .196 3.060 1.118

294 2 1** .577 1 .523 .311 2 .477 .497 -.074

295 2 1** .735 1 .773 .115 2 .227 2.567 -.971

296 2 2 .642 1 .553 .216 1 .447 .638 .167

297 2 2 .584 1 .526 .300 1 .474 .512 .084

157

298 2 2 .170 1 .926 1.880 1 .074 6.939 2.003

299 2 2 .954 1 .674 .003 1 .326 1.455 .574

300 2 2 .158 1 .930 1.995 1 .070 7.159 2.044


Classification Resultsa

sex

Predicted Group

Membership

Total 1.00 2.00

Original Count 1.00 107 43 150

2.00 30 120 150

% 1.00 71.3 28.7 100.0

2.00 20.0 80.0 100.0

a. 75.7% of original grouped cases correctly classified.

158

BIOGRAPHY

Name-Surname (Thai) : นางสาวเกวล พมเกษร

(English) : MISS KEOWALI PHUMKESON

Student Number : 53312302

Present Degree : Master of Science in Forensic Science

Silapakorn University

Connect Place : Bumrungrad International Hospital

E-mail address : [email protected]

Telephone : 086-8348808

Documents

STATURE ESTIMATION AND SEX DETERMINATION: AN …