CMSC 838S Information Visualization Spring 2006 Assignment 1

CMSC 838SInformation Visualization

Spring 2006Assignment 1

Static Displays of Census Data

Abhinav Gupta

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1950 1960 1970 1980 1990 2000 2003Year

Age-wise breakup of resident population

> 85yrs

75-84 yrs

65-74 yrs

55-64 yrs

45-54 yrs

35-44 yrs

25-34 yrs

15-24 yrs

5-14 yrs

1-4 yrs

< 1yr

Between 1950 and 2003, the U.S. population grew older. The population 75 years of age and over grew 2.9 times as quickly as the total population.

In recent decades the percent of the population that is of Hispanic origin or Asian has more than doubled. In 2004, more than 30% of the population identified themselves as Hispanic, black, Asian, American Indian or Alaska Native, or

Native Hawaiian or Other Pacific Islander.

Poverty by Age (1966-2003)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Year

Percent

Prior to 1974 people of 65yrs and above well more likely to be poor. The poverty rate of older Americans has declined rapidly. Children are more likely to be in

poverty than the working-age and old-age Americans.

Adam Phillippy

Prenatal care tendencies for mothers of differing ages

0

5

10

15

20

25

30

35

40

45

50

1st month 2nd month 3rd month 4th month 5th month 6th month 7th month 8th month 9th month No prenatalcare

Month prenatal care began

%of births

15-24 yrs. old

25-34 yrs. old

35-44 yrs. old

Data: Very young mothers seek prenatal care later than other mothers.

Visualization: I usually don’t like clustered bar charts because it’s not always obvious what’s going on, but for this case I failed to find another way to display the three age

groupings simultaneously without readability problems.

http://wonder.cdc.govAdam Phillippy

Data: Uneducated mothers seek prenatal care later than other mothers.

Visualization: It’s easier for my eye to compare continuous distributions, but maybe not for the average reader. This line plot gives me a better “first impression” over the

clustered bar chart, but only when dealing with a few categories.

Adam Phillippy http://wonder.cdc.gov

Prenatal care tendencies for mothers over 20 of differing education

0

10

20

30

40

50

60

1st month 2nd month 3rd month 4th month 5th month 6th month 7th month 8th month 9th month No prenatalcare

Month prenatal care began

%of births

0-12 yrs. eductation

13-16+ yrs. education

Top causes of male deaths over the past 20 years

0

20

40

60

80

100

120

140

160

180

Heart attack

Coronary disease

Lung cancer

Stroke

Cardiovascular diseasePulmonary disease

Ischemic heart disease

Colon cancerPneumonia

Deaths per 100,000

1979-1982

1983-1986

1987-1990

1991-1994

1995-1998

Adam Phillippy http://wonder.cdc.gov

Data: Heart disease is on the decline, but the rest are steady or increasing.

Visualization: Back to the clustered bar charts, but this time clustering categories instead of time points. Change over time was my main interest, so clustering by

category makes the most sense for spotting changes. (Category names are rough translations)

Estimated Life Expectancy in United States, 1900 – 2002

Chang [email protected]

1. Growing trend in the past century

2. Life expectancy between women and man

3. Life expectancy between white and black

For both sex and all races, estimated life expectancy is gradually growing from the year 1900 to 2002. The influenza in 1918 may be responsible for a sudden drop in estimated life expectancy. After 1945, there are fewer fluctuation, which may be due to a time without world wars, or the establishment of the States' position as a leading country.

1. Est i mated l i f e expectancy at bi rth i n years, Death-regi strat i on States, 1900_ 28, and Uni ted States, 1929_ 2002

0. 0

10. 0

20. 0

30. 0

40. 0

50. 0

60. 0

70. 0

80. 0

90. 0

19001904190819121916192019241928193219361940194419481952195619601964196819721976198019841988199219962000Year

Age1918

Women generally live longer than men. The differece of estimated life expectancy reached its peak on 1980, and has been gradually decreasing for the following 20+ years.

2. Compari son of esti mated l i fe expectancy for mal e and femal e,Uni ted States, 1900_ 2002

0. 0

10. 0

20. 0

30. 0

40. 0

50. 0

60. 0

70. 0

80. 0

90. 0

19001904190819121916192019241928193219361940194419481952195619601964196819721976198019841988199219962000Year

Age

0

1

2

3

4

5

6

7

8

9

al l f emal e

al l mal e

femal e-mal e di f f .

Ag

e d

iffe

ren

ce

African American's life expectancy is significantly lower than average, whereas white people's life expectancy is slightly higher than average. This has been true for at least the past century.

Derek Juba

1940 1950 1960 1970 1980 1990 2000 20100

20

40

60

80

100

120

140

160

U.S. Syphilis rate (all types)

Year

Cas

es p

er 1

00k

peop

le

U.S. Syphilis rates have been generally dropping since 1950, except for a spike around 1990. Data reporting frequency increased in 1988.

Derek Juba

1940 1950 1960 1970 1980 1990 2000 20100

1

2

3

4

5

6

7

8

9

10

U.S. Congenital Syphilis rate

Year

Cas

es p

er 1

00k

peo

ple

U.S. Congenital Syphilis rates are similar to overall Syphilis rates, generally dropping since 1950 except for a spike around 1990. Data reporting frequency also increased in 1988.

Derek Juba

1940 1950 1960 1970 1980 1990 2000 20100

50

100

150

200

250

300

350

400

450

500

U.S. Gonorrhea rate

Year

Cas

es p

er 1

00k

peop

le

U.S. Gonorrhea rates increased from 1960 to 1980, but have since dropped back down to 1960 levels. Reporting frequency increased in 1988. Gonorrhea rates do not show much correlation to Syphilis rates.

Derek Juba

Pedal Cyclists Killed By Motor Vehicle

Gleneesha Johnson

CMSC 838S


0

50

100

150

200

250

1981 1983 1985 1987 1989 1991 1993 1995 1997Year

Number Killed

0-4

5-9

10-14

15-19

20-24

The number of very young, ages 0-4, pedal cyclists killed by cars has remained pretty low and constant over the years. This is probably due to the fact that they can’t yet ride a cycle and if they can, they are very closely supervised. There is generally a decreasing trend seen from ages 5-24, with the most dramatic drop seen by children 10-14.

Every year between 1981-1998, at least four times more Male cyclists were killed by cars than Female cyclists.

0

100

200

300

400

500

600

700

800

Number Killed

1981 1984 1987 1990 1993 1996

Year


Male

Female

Pedal Cyclists Killed By Motor Vehicle from 1981-1998

82%

15%

1%

2%

White

Black

Am Indian/AK Native

Asian/Pac Islander

The overwhelming majority of pedal cyclists killed by motor vehicle between 1981 and 1998 were White.

Georg Apitz

CMSC 838S © by geapi , 2006

Population Changes

Increase in Population by Race in the U.S.

0

5000

10000

15000

20000

25000

30000

35000

40000

1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Year

Number of People in Thousands

Hispanic

Black

White

- increase in population

- white and hispanic increasing

- black almost constant

Increase in Salary by Race

0

2

4

6

8

10

12

14

16

1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Thousands

Year

Salary (Median)

White

Black

Hispanic


Salary Changes- general increase

- black and hispanic similarily increasing

- highest salaries for white


Salary at Certain Points- general increase

- black and hispanic similarily increasing

- highest salaries for white

Salary at 4 Points in Time over 30 years

0

2

4

6

8

10

12

14

16

1976 1986 1996 2003

Thousands

Year

Salary (Median) in $

White

Black

Hispanic

Cancer Incidence in the US

Hamid Haidarian Shahri

Data provided by:

National Program of Cancer Registries Invasive Cancer Incidence

URL: http://wonder.cdc.gov/controller/datarequest/D11

Cancer Incidence Rate for Different Races

Age-Adjusted Cancer Incidence Rate Per 100000for Different Races

0

100

200

300

400

500

600

Asian or Pacific Islander Black or AfricanAmerican

White

Why is cancer less common in Asians?

Why is cancer less common in Asians?

Cancer Incidences at Various Ages

• 70-74 is the riskiest age group for cancer,and men are at a higher risk than women.

Cancer Incidences for Various Age Groups

0100000200000300000400000500000600000700000800000

< 1 year5-9 years15-19 years25-29 years35-39 years45-49 years55-59 years65-69 years75-79 years

85+ years

Age Groups

Cancer Incidences

Female

Male

Cancer Incidence Rate Per 100000in Various States

• Where should we be living, or does it really matter?

Change and difference in obesity among different states in US:

(1) change in 8 years of gap (2) difference between gender

Hyunyoung Song2006 Spring 838S Info Vis

States with least obesity problem

0 5 10 15 20HawaiiColorado

New Mexico

ArizonaMontana

OregonMarylandMassachusetts

Rhode Island

Wyoming

ArkansasWashington

Obese/Overweight

diff2001-20031993-1995

States with most obesity problems

0 5 10 15 20 25 30

Wisconsin

Delaware

Illinois

Mississippi

Pennsylvania

Louisiana

Ohio

Iowa

North Dakota

District of Columbia

Alaska

Michigan

Obese/Overweight

diff2001-20031993-1995

• In 8 years, people became more obese with range of 2.3% (Alaska) to 12.4% increase (Michigan).

• Average of 15~22% of the population are obese in United States in year 2003.

Change in obesity in 8 years of gap (1)

• There are less Obese/Overweight people near coastline and mid-west.

• States around lake Erie are high in obese population.

Change in obesity in 8 years of gap (2)

• In red tone states female are more obese than male in general. Notice that Maryland is one of them.

• In blue tone states, male are more obese than female.• In more than half of the states, male are overweight compared to

women.

Difference in obesity in different states

Maryam Farboodi

The total number of deaths caused by injuries has generally dropped during this decade (in spite of the slight rise toward the end). The decrease has

essentially been in the number of male victims as number of female victims remained nearly the same throughout the whole period. The interesting point

is that number of male victims is nearly four times number of female ones!

Maryam Farboodi

Injury Mortality of All Causes by Sex Age Range: 25- 44, Nationwide

0

10000

20000

30000

40000

50000

60000

1992-1994

1993-1995

1994-1996

1995-1997

1996-1998

1999-2001

2000-2002

Year

Number of Victims

female

male

As the chart shows, the most important causes of injury mortality in US are firearms, motor-vehicle traffic and poisoning. Number of firearm deaths has a decreasing trend over the decade under consideration so that although there is no considerable change in number of traffic deaths, it became the

most common cause over the end of the decade. Moreover, number of deaths caused by poisoning has constantly risen and ranked two after

traffic deaths in the last two years.Maryam Farboodi

Different Causes of Injury Mortality by Year Age Range: 25- 44, Nationwide

02000400060008000

1000012000140001600018000

1992-1994

1993-1995

1994-1996

1995-1997

1996-1998

1999-2001

2000-2002

Year

Number of Victims

Motor-vehicle traffic

MVT-pedestrian

Fall

Suffocation

Fire/hot object/substance

Firearm

Poisoning

Number of suicides has been nearly unchanged for many years and has only slightly decreased in the last three years. On the contrary, number of unintentional mortal injuries has increased in the same period. Number of murders has dropped

34% during the above 10 years. Interestingly, number of suicides has been constantly greater than number of murders!

Maryam Farboodi

Mortal Injuries Classified by Intent/Manner Age Range: 25- 44, Nationwide

0

5000

10000

15000

20000

25000

30000

1992-1994

1993-1995

1994-1996

1995-1997

1996-1998

1999-2001

2000-2002

Year

Number of Victims

Unintentional

Suicide

Homicide

Cancer Death Rates

Michael Schatz

2/2/2006CMSC 838S Information Visualization

Cancer Deaths by EthnicityOverall Cancer Deaths by Ethnicity

(age adjusted per 100,000 standard population)

0

50

100

150

200

250

300

1998 2001 2004 2007 2010

Year

Deaths

American Indian or Alaska Native

Asian or Pacif ic Islander

Black or African American

White

Hispanic or Latino

Black or African Americans have the highest cancer death rate, and is almost twice as high as the ethnicity with the lowest cancer death rate, that of Asian or Pacific Islanders. Fortunately, there is a decreasing trend for all ethnicities aimed at or below the rate targeted for 2010. It is hard to rule out genetic biases, lifestyle/cultural differences, access to medical care, or other factors as the cause of the discrepancy without additional information.

ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/DATA2010/FOCUS03.XLS

Cancer Deaths by GenderOverall Cancer Deaths by Gender


0

50

100

150

200

250

300

1998 2000 2002 2004 2006 2008 2010 2012Year

Deaths

Female

Male

The cancer death rate is considerably higher in males than in females. Female will easily reach the targeted 2010 rate, while males will require a 45% reduction in the cancer death rate. Genetic bias and lifestyle differences are the likely explanations for the discrepancy, since other factors, especially access to medical care, should be balanced between genders.


Cancer Deaths by EducationOverall Cancer Deaths by Education


020406080

100120140160180

1999 2000 2001 2002 2003

Year

Deaths

Less than high school

High school graduate

At least some college


People that have attended some college have approximately ½ the cancer death rate than those that have not for all years in the study. Furthermore, the rate for people with some college education dropped slightly during these years, while it rose slightly for the others. This is presumably because college education correlates with a higher standard of living and access to medical care, rather than the lifestyle experienced while in college.

Mudit Agrawal([email protected])

Datasets used:

http://lib.stat.cmu.edu/

http://www.cdc.gov/nchs/Default.htm

http://lib.stat.cmu.edu/

https://po2.mail.umd.edu/cgi-bin/fetch.cgi?url=http%3A%2F%2Fwww.cdc.gov%2Fnchs%2FDefault.htm%29








The graph clearly shows why mammals like Man, Horse are known as active species – their ratio of sleep to lifebeing the lowest. On the other hand, opossum, guinea pig sleep much more. No doubt, sleep like a pigand run like a horse come in our vocabulary!

Life Span : Sleep in Mammals

African elephant

African giant pouched rat

Arctic Fox

Asian elephant

Baboon

Big brown bat

Brazilian tapirCat

Chimpanzee

Chinchilla

Cow

Donkey

Eastern American mole

Echidna

European hedgehog

Galago

Genet

Giant armadillo

Goat

Golden hamster

GorillaGray seal

Gray wolf

Ground squirrel

Jaguar

Lesser short-tailed shrew

Little brown bat

MouseMusk shrew

N. American opossumNine-banded armadillo

Owl monkey

Patas monkey

Phanlanger

Pig

Rabbit

Raccoon

Rat

Red fox

Rhesus monkey

Rock hyrax (Hetero. b)Rock hyrax (Procavia hab)

Roe deer

Sheep

Slow loris

Star nosed moleTenrecTree hyrax

Tree shrew

Vervet

Water opossum

Guinea pig

Horse

Man

0

20

40

60

80

100

120

Life Span in Years Hours of Sleep per day

Due to color-similarity between the PIE and names, the confusion between lower % causes is avoided.It is clear that Congenital Anomalies and Short Gestation are among the main reasons of death in infants,whereas Circulatory, respiratory diseases etc. are very not that serious and prominent. Does that mean, deaths are mainly due to anomalies present before births?

Living Arrangements (age 25-34)

0

10

20

30

40

50

60

70

80

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Percentage of people per year

Living alone

Living with spouse

Living with other relatives

Living with non relatives

There is a clear decline in ‘living with spouse’ at the age of 25-34. There is also an increase in living with other/non relatives. This may be either due to people getting married at later ages or because of frequent breaking of relationships. Since living alone is nearly constant, the former reason is more probable.

Assignment 1Living Arrangement data of US

population by age and sex

Neeti Ogale

1980 1985 1990 1995 2000 200550525456586062646668707274767880

Percentage of population living with spouse

(Male and Female)

Year

Age:35-44 Age:45-54 Age:55-64 Age:65+ Age:25-34

Percentage of people of different age groups who live with spouse

It can be seen that percentage of people of age above 60 that live with spouse is increasing. But for all other age groups, the percentage is decreasing over the years.

1980 1985 1990 1995 20000

10

20

30

40

50

60

70

80

Percentage of population Age: 35-44

(Male and Female)

Year

Living alone Living with spouse Living with relative Living with non relative

Data of living arrangements for people of age 35-44

It can be seen that percent of people within age 35-44 living with spouse is decreasing while those living with relatives and alone is increasing over the years.

1980 1985 1990 1995 2000

0

10

20

30

40

50

60

70

80

90

100

Percent of male population of age: 35-44

Year

1980 1985 1990 1995 20000

10

20

30

40

50

60

70

80

90

100

Percent of female population of age: 35-44

Year

Living with spouse

Living with relative

Living alone

Living with non relative

Data for female and male of age 35-44

More percent of Malepopulation than female population is living alone,and this is fairly constantover period of 20 years. More of Female populationIs living with relatives thanMale over the period of 20 years.

MALE

FEMALE

Factors In Polio Vaccination Falling Behind Schedule

Nicholas Chen

Mother’s Education Level

NOTE CROPPED Y AXIS. Current polio vaccination guidelines suggest that children be given three vaccination doses by 18 months of age. We would like to examine the factors that may cause a child to fall behind the recommended vaccination schedule. All data sets use vaccination data for children aged 18-35 months. Here, we see that the highest level of education attained by the mother (or female guardian) correlates with the likelihood a child will be on schedule. A similar trend is seen when we bin using the age range of the mother, which should not be surprising, because women having children at older ages tend to be better educated.

Distribution of Polio Doses Received by Mother's Education Level

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Some HighSchool

High School Some College College

Mother's Education Level

Three or more doses

Two doses

One dose

No doses

Number of Children In Household

NOTE CROPPED Y AXIS. Another possible factor would be the number of other children in the household. One might expect that families who have had more experience with young children and required vaccinations would tend to stay on schedule. However, we see that the opposite is true. Possible reasons may be that parents are too busy with multiple children. Or, they grow complacent with sticking to a strict vaccination schedule.

Distribution of Polio Doses Received by No. of Children In Household

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

1 Child 2-3 Children 4+ Children

Number of Children In Household

Three or more doses

Two doses

One dose

No doses

Income

NOTE CROPPED Y AXIS. Surprisingly, except for incomes at the extremes, there does not appear to be a strong correlation between income levels and adherence to the recommended vaccination schedule. The reason for this may be that the income is a aggregate household income, and not necessarily a reflection on the primary caretaker of the child.

Distribution of Polio Doses Received, by Household Income

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

$0-$7500

$7501-$10000$10001-$12500$12501-$15500$15501-$17500$17501-$20000$20001-$25000$25001-$30000$30001-$35000$35001-$40000$40001-$45000$45001-$50000

$50001+

Household Income

Three or more doses

Two doses

One dose

No doses

Rachael Bradley

Asthma Related Deaths 1998-2002

0100020003000400050006000700080009000

100001100012000130001400015000

1998-2000 1999-2001 2000-2002Years

Number of Deaths

0-4 5-17 18+ Age:

The majority of asthma related deaths occur in individuals over the age of 18. Relatively few occur

before the age of 4. The number of asthma related deaths has decreased since 1998.

The majority of asthma related deaths occur in individuals over the age of 18. Relatively few occur

before the age of 4. The number of asthma related deaths has decreased since 1998.

Number of Asthma Related Deaths by State (1998-2002)

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900

WyomingVermont

AlaskaRhode Island

D.C.North Dakota

MaineDelaware

IdahoMontana

New HampshireSouth Dakota

NevadaHawaii

West VirginiaNew Mexico

UtahKansas

NebraskaIowa

ConnecticutOklahomaArkansas

MississippiKentuckyColorado

OregonSouth Carolina

AlabamaIndiana

LouisianaWisconsin

ArizonaMissouri

MarylandMinnesota

WashingtonMassachusetts

TennesseeVirginia

New JerseyGeorgia

North CarolinaMichigan

OhioPennsylvania

FloridaIllinoisTexas

New YorkCalifornia

Number of Deaths

1998-2000

2000-2002

California had the highest number of

asthma related deaths in both the 1998-2000 and the 2000-2002 range. It also had the

largest decrease in

deaths between those years.

California had the highest number of

asthma related deaths in both the 1998-2000 and the 2000-2002 range. It also had the

largest decrease in

deaths between those years.

Change in Asthma Related Deaths Between 1998-2000 and 2000-2002

TennesseeUtahNew Jersey

FloridaWashingtonAlabamaDelawareMississippiOhioNew HampshireIowaAlaskaSouth DakotaWyoming

Rhode Island

Arkansas

West Virginia

VermontMaryland

South CarolinaConnecticut

NebraskaNew Mexico

MontanaMaine

HawaiiGeorgiaKentucky

North DakotaLouisiana

Nevada

OklahomaKansas

D.C.Idaho

Oregon

MinnesotaWisconsinColorado

North CarolinaMassachusetts

MissouriArizona

Pennsylvania

VirginiaMichiganIndianaIllinois

New YorkTexas

California

-220-210-200-190-180-170

-160-150-140-130-120-110-100

-90-80-70-60-50-40-30-20

-100

10203040

California had the largest decrease in asthma related deaths while Tennessee had the largest increase.California had the largest decrease in asthma related deaths while Tennessee had the largest increase.

Samah Ramadan

0.0

5.0

10.0

15.0

20.0

25.0

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Year

Percentage

All races

White

Black or African American

American Indian or Alaska Native

Asian or Pacific Islander

Hispanic or Latino

Declining rate of smoking mother except for native Americans where decline is slower.

Mothers smoking during pregnancy categorized by race

Samah RamadanSamah Ramadan

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1997 1998 1999 2000 2001 2002 2003

Male -Severe headache or migraine

Female- Severe headache or migraine

Male- Low back pain

Female- Low back pain

Male- Neck pain

Female- Neck pain

Females in general suffer from different types of pain more than males.

Headache, migraine, low back pain and neck pain among adults.

Samah Ramadan

Scott Nestler

Scott Nestler, CMSC 838S, Assignment 1, 31 JAN 2006, Slide 1 of 3Source: 2004 National Immunization Survey, National Center for Health Statistics, http://www.cdc.gov/nchs

Average Time to Vaccination

0 50 100 150 200 250 300 350 400 450 500

MMR

VRC

PCV

POLIO

HIB

DTP

HEPB

Vaccine

Age (in days)

Not

Firstborn

It appears that, in general, parents get their firstborn childvaccinated in a more timely manner than subsequent children.


Boys and girls receive the recommended vaccinationsat approximately the same rates.

Male

Yes

47%

No

38%

Don't Know

15%

Refused

0%

Yes

No

Don't Know

Refused

Female

Yes

46%

No

39%

Don't Know

15%

Refused

0%

Yes

No

Don't Know

Refused

Gender Impact on Immunizations

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

Percentage of Responses

Yes No Don't Know Refused

Is Child Current on Immunizations?

Widowed/Divorced Never Married Married


Children of parents who are(or have been) married aremore current on recommendedimmunizations. Similar resultscan be shown for mother’seducation and income levels.

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

1974-79 1980-82 1983-85 1986-88 1989-91 1992-2000

White Both Genders

White Males

White Females

Balck both genders

Black Males

Black Females

Generally increasing survival rate. Rate is higher in whites than blacks.

Cancer survival rate categorized by race and gender

Samah Ramadan

Timur Chabuk

1-1011-20

21-3031-40

41-5051-60

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

Number of Deaths

Age at Death (Years)

Top 5 Causes of Death (Accidental Injury) 1999-2003

Drowning

Fire

Fall

Poison

Motor Vehicle

In this graph you can see that particular types of injuries cause deaths in some age groups more than others. Unsurprisingly, the number of fatal injuries caused by falling down is higher in older age groups. Though slightly more subtle, one can see that the number of fatal injuries caused by fires is higher among young and old age groups than among middle aged groups. Deaths from motor vehicle related injuries are much more numerous in the 10-20 age group than the 1-10 age group. (Timur Chabuk)

Top 5 Causes of Death (Accidental Injury) 1999-2003 by Gender

0

20000

40000

60000

80000

100000

120000

140000

Motor Vehicle Poison Falling Drowning Fire

Cause of Death

Number of Deaths

Female

Male

Its clear from this graph that more men than women die from accidental injuries. One could imagine reasons that more men than women die from traffic accidents, but the fact that more men than women die from poisoning is quite peculiar. (Timur Chabuk)

Top 5 Causes of Death (Accidental Injury) 1999-2003, Percent by Cause

60%

25%

5%

5%

5%

Motor Vehicles

Poison

Falling

Drowning

Fire

An overwhelming majority of accidental deaths from injuries come from motor vehicle accidents. I was quite surprised by the number of deaths caused by poisoning (25%). (Timur Chabuk)

Vlad Morariu

Mean Income of Males and Females of Age 45-54

0

10000

20000

30000

40000

50000

60000

197419751976197719781979198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003

Year

Income (dollars)

Male

Female

Here we can see that the mean income of males and females aged 45-54 has been increasing steadily since 1974 for both groups. We notice that the income of males is still much higher than that of females, though we can see that in 1974 the income of males was roughly double that of females, but less than double in 2003.

Vlad Morariu

Mean Income of Persons 65 and Older in 2003 Dollars

0

5000

10000

15000

20000

25000

30000

1976197719781979198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003

Year

Income (2003 adjusted dollar value)

White

Black

Hispanic

Here we see that the mean income of Whites aged 65 and above is higher than that of Blacks and Hispanics from 1976 to 2003. However, as a percentage of the income of the Whites, the income of Blacks and Hispanics has been increasing. Also, we note that starting in 1995, the income of Blacks surpassed that of Hispanics.

Vlad Morariu

Mean Income by Age Group in 2003

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5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

25-34 35-44 45-54 55-64 65-74 75 and over

Age Group

Mean Income

White

Black

Hispanic

We see that for 2003 the disparity in income between Whites and both Blacks and Hispanics is greatest in the 45-54 age group. Also, the three groups maintain their relative position through all age groups shown above. That age group also has the highest overall income. Does the fact that the mean income in the 55-64 group is lower than the 45-54 group imply that there are many who retire before age 65?

Vlad Morariu

Nathanial Ayewah

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6.0

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12.0

Deaths per 100,000 workers per year

5,000

5,500

6,000

6,500

7,000

7,500

8,000

8,500

9,000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Deaths per year

Nat AyewahNat AyewahUS Occupational Injury Deaths and Rates: 1992 - 2002US Occupational Injury Deaths and Rates: 1992 - 2002 Source: http://www.cdc.gov/nchs/fastats/osh.htm

Including fatalities from Sept 11, 2001

Rate Rate versusversus Actual Count Actual Count

The first graph shows a steady decline in the rate of occup-ational deaths from 1994. This trend is more unstable in the second graph because the “deaths per year” depend on the size of the workforce that year.


Rate Rate versusversus Actual Count Actual Count

At first glance, the rate of deaths indicates that Mining and Agriculture are the most dangerous industries while the Retail and Services industries are quite safe.

But the latter two industries contribute many more deaths than the first two because they employ more people.

So where should a polititian place his or her focus?

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10.00

15.00

20.00

25.00

30.00

Deaths per 100,000 workers

Average 1992-2002 2002

2002 was better than the average over this period in almost all industries!


Thought the rate of death among white workers is comparable to the rates of other races, they make up almost 75% of the actual deaths per year. Many factors could account for this including the size of the workforce and the nature of employment.

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1.00

2.00

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White Black or AfricanAmerican

Hispanic or Latino

Deaths per 100,000 workers

Documents

CMSC 838S Information Visualization Spring 2006 Assignment 1