Phase III Completed

8/3/2019 Phase III Completed

http://slidepdf.com/reader/full/phase-iii-completed 1/26

Running head: Class Survey 1

Class Survey Data Analysis Stats 1510 (Day)

Kimberly Rivera

Statistics 1510

Professor Brian Jean

December 12, 2011

Taft College




Abstract

In this experiment I my class and I surveyed a random ten people each in order to gather

information concerning the connections of the society we live in. In order to analyze correlations

in our society we sought out the relationships of between social characteristics and opinions: the

height of a respondent and it's relationship to their shoe size, the difference in gross income

based on gender, and whether there is a relationship between handiness and favor of death

penalty and water consumed; as well as, the relationship between political party and if the

respondent feels President Obama should be re-elected, if the respondent is in favor of the death

penalty, and if the respondent is in favor of the health care bill being passed. Furthermore, I

hypothesized that political party change and ethnicity were related, as well as ethnicity and the

carrying of the HIV infection. I found that a majority of my hypothesis were correct with the

exception of some such as annual gross income and genders, and political party and Obama’s

reelection. Overall this study stands to disprove absurd correlations within society that are

otherwise considered true.

Introduction

The relationship between two circumstances and their effects on each other are of the up

most importance when observing society around us. In this experiment I am determining the

correlation between many variables and how they shape societal factors between individuals.

Height and shoes size were calculated in order to compare the correspondence between

both. I hypothesize that the height of a person and their shoe size are related. For example, the

taller one is the larger their foot size will be as opposed to the short person with small feet.

Additionally, the weight of a person and their ring size are correlated, I believe. Such as, if a




person is a of bigger bone structure then their weight will be higher than those whom have

smaller frames; transversely this effects the ring size, bigger boned people will have a larger ring

size.

The difference of gross income between genders has been the topic of much controversy,

leading me to my next theory on our society. My hypothesis regarding the difference between

male and female gross income is that there is no significant difference between the both. In this

day and age a female has just as many opportunities laid out before her as a male does. The idea

that a male earns more than a female may have been true in history past, but is a primitive way of

thinking in this present day.

Political parties serve as a mean to group those who have similar political views together

in order to reinforce those views. I hypothesize that there is a firm relationship between one’s

political party and whether they will re-elect Obama, pass the health care bill, and if they are in

favor of the death penalty. These three decisions are correlated with one’s political party because

the views of the voter are mainly related to that of their party, and each party differs in opinion.

There have been studies done concerning the fairly common, yet still unusual, left-

handedness trait some people posses. Even more uncommon is the ability to use both hands with

equal strength, known as being ambidextrous. The possibility of handedness and whether one is

in favor of the death penalty being related was calculated. Furthermore, the relationship between

handedness and water consumption was also tested. My hypothesis is that handedness has no

relationship with either favor in death penalty or water consumption.

Taft College is a diverse campus, and the many ethnicities may have to do with the

change in affiliation with political parties and the carrying of the HIV infection. My hypothesis is




that ethnicity does not have any correlation with the change in affiliation of political party.

However, I do believe that ethnicity has to do with the carrying of HIV infection.

With the data collected I will test my hypotheses and determine their relevance; all the

while coming one step closer to discovering the connections of our society.

Methods

1) Materials

- Stats 1510 Survey Worksheet

- A Black Ink Pen

- TC Stats App for IPad

- One Quarter (assumed to be fair)

- Access to internet

2) Participants

Myself as the data analysis specialist and a total of 40 randomly selected people, 13 females and

37 males.

3) Procedure

10 copies of the Stats 1510 Worksheet (see image 1.) were printed. A simple random sampling

technique was used to determine who our team would ask to fill out the survey. A quarter

(assumed to be fair) was flipped, heads being every consecutive person and tails representing

every other person. The quarter landed tails up, thus every other person was to be asked. Every

other person who entered the Taft Library was asked to fill out the survey. Once ten total surveys

had been filled the data for each survey was entered online at http://tinyurl.com/2v3tkur . This

was done a total of ten times, following the specific directions shown on the worksheet. Once the

http://tinyurl.com/2v3tkur






total amount of survey data was entered, twenty five hundred people had been surveyed. A

sample was taken from this total by conducting a random number sample on TC-Stats, resulting

in 40 participants to analyze. The process for performing the random selection of a sample is

simple: create a new column called “random” and click on it tab, select random and set the lower

bound to 1 and the upper bound to 2500; make sure to start row at 1 and stop row at 40. The

randomization and narrowing of the population is crucial in order to ensure a fair sample,

reducing chance error. The sample was then reviewed and found to have errors due to the input

of data. The corrections necessary for the analysis to move forth were made and the data was

then ready to be analyzed.

Results

I was surprised by some of the results upon completion of this experiment. The first test

was not too much of a shocker. I had hypothesized that the height of a person and their shoe size

are related, and found statistical evidence (p-value= 0.0350) proving so. I came to this

conclusion by testing height and shoe size with a scatter plot and found it to be monotonic (see

Fig. 16.1). I thus began to use spearman’s equation and found the conclusion to match my

hypothesis.

When testing whether weight and ring size had a relationship, in the second part of the

first quest (see Fig. 16.2), I found that my hypothesis was proven wrong. Based on the statistical

evidence (p-value= 0.0817), found through spearman’s equation as well, I concluded that there

was in fact not enough evidence to suggest a relationship between weight and ring size.

I hypothesized that there was no difference between the gender’s and their annual gross

income and was astonished to be proven wrong by my sample. After conducting a Wil-cox Rank

Sum (see Fig.16.3), the statistical evidence (p-value: 0.0003) was overwhelming in pointing




towards the disproving of my hypothesis. There was in fact enough evidence to suggest that there

is a difference in gender and their gross incomes.

My hypothesis matched all the results pertaining to the political party questions. The

relationship between political party and if the respondent was in favor of reelecting Obama was

proven to be dependent. My hypothesis mirrored the results after I performed a Chi-squared test

of independence and found the two to be dependent due to the statistical value (p-value: 0.0035)

falling below alpha (see Fig. 16.4). Political party and favor of health care and death penalty

were both found to be dependent as well (see Fig. 16.5 & 16.6).

I was completely wrong with my hypothesizes having to do with handedness.

Handedness and favor in the death penalty held a statistical value of p-value= 0.3430, causing

there to be enough evidence to suggest dependency. Furthermore, handedness and consumption

of water where found to be correlated despite my belief otherwise, containing a p-value of

0.0000; which allowed for sufficient evidence to prove a correlation.

Discussion

My observations regarding the heights of my sample size (n) is represented through the

histogram Fig 1.1. The histogram is relatively bell-shaped with a class width of 3.5 and a starting

point of 50. The summary statistics, retrieved through TC- Stats, are shown in Fig. 1.2: Mean=

65.875, Median= 66, and standard deviation=5.552. Because of the bell-shape, the graph is

distributed symmetrically; therefore, the mean is the appropriate measurement of center.

Fig. 1.1




Fig. 1.2

In terms of Weight, the histogram representing the sample data (Fig. 1.1, following page)

is skewed right with a class width of 29.1250 and a starting point of 77. The summary statistics

report a mean of 180.325, a median of 172.5, and a standard deviation of 5.516. The right skew

of the data shows that the median will be used for the measurement of center.




Fig. 2.1

Fig. 2.2

The ring size amongst the sample is somewhat symmetrical, as shown in Fig. 3.1 (on the

following page). The histogram is approximately bell-shaped and has a class width of 1.5 and a

starting point of 3. Fig. 3.2 states the summary statistics: mean= 7.775, median= 8, and standard

deviation= 2.423. The symmetry of the data points to the center of measure to be that of the

mean.




Fig. 3.1

Fig 3.2

The shoe sizes within our sample are presented in Fig. 4.1(on the following page). This

graph shows that the data is approximately bell-shaped, making it symmetrical, with a class

width of 2 and a starting point of 3. Because of this we know the measurement for center will be

the mean. The summary statistics are given in Fig. 4.2 with a mean of 8.7625, a median of 8, and

a standard deviation of 2.454.




Fig. 4.1

Fig. 4.2

The graph shown in Fig. 5.1 on the following page reveals the histogram for the sample

data regarding the gross income of males. The data is skewed right and its class width is 13000

with an identical starting point of 13000. The measurement of center would be the median

because of the graph being skewed right. The summary statistics are shown in Fig. 5.2, showing

a mean of 28777.78, a median of 34000, and a standard deviation of 27337.4.




Fig.5.1

Fig. 5.2

The annual gross income for females is represented in the graph in Fig. 6.1 (following

page). The data is approximately bell shaped and symmetrical, meaning the measure of center is

the mean. The class width is 13500 with an identical starting point of 134500. Fig. 6.2 tells the

summary statistics of the graph: mean= 55076, median= 5100, and standard deviation=

17736.32.




Fig. 6.1

Fig. 6.2

Fig. 7.1, on the following page, depicts those who would, wouldn’t, or are undecided on

whether or not they will reelect the Obama. Over half of the sample said they would not reelect

Obama, a total of 52.50% out of forty people. 20% of the sample was undecided and 27.50%

said they would reelect Obama. Considering that almost half my sample are Democrats, these

statistics are surprising.




Fig. 7.1

The political party of each individual from within my sample of forty was recorded and can be

seen in a graph in Fig. 8.1. The majority of the sample were Democrats, at 40%. Following right

behind are the Republicans at 30%. Independents were 20% and other parties made up the

remaining 10%. Though Democrats win majority republicans are not far behind in numbers.

Fig. 8.1




Based on Fig. 9.1, very close to half of those asked in the sample vote no on passing the

health care bill at 47.5%. 30% of them are undecided regarding the bill, and only 22.5% vote yes

on passing the bill. Again this is surprising due to the number of Democrats who took part in this

survey.

Fig. 9.1

In Fig. 10.1, it is shown that undecided is not even valid as a decision, all forty of the

sampled had their minds made up regarding the death penalty, which I expected due to the

dominance of Democrats and Republicans in the sample, who stand by their party’s belief’s.

Over half of the sample voted yes on the death penalty, 67.5%, and 32.5% voted no. Considering

that over half of our sample is Democratic, this can lead to a more radical response to the

questions asked on the survey.






Fig. 12.1

Fig. 12.2

The graph in Fig. 13.1 represents those who have a change in political party. More than

half of the sample, 67.5%, stated that a change in party is not applicable to them, meaning they

stayed with their original affiliations. 17.5% said they considered themselves to be Democrat and

now side with the Tea Party, 12.5% thought themselves to be Republicans but associate with the

tea party now and lastly 2.5% of those who believed they were other than Democrat and

Republican are now affiliated with the Tea Party.




Fig. 13.1

Fig. 14.1 represents those within the sample of forty who have HIV infection. 67.5%,

which is more than half of those asked in the sample, said that they did not have HIV. However,

32.5% said that they did have HIV infection, but this shouldn’t have an effect on the answering

of the survey questions.

Fig. 14.1

The ethnicities of the forty sampled are represented in the graph in Fig. 15.1. The highest

percentage, 72.5% were white, and Hispanics followed at 2.5%. 5% were filled by the category




of black and other. Such a high percentage of the white ethnicity was not expected and may have

an effect on how the survey questions are answered, leaning towards more of a white mentality.

Fig. 15.1

Appendix

Phase II

• The sample size (n) is forty for all the previous graphs and data collected.

• In order to collect my sample I used Simple Random Data. TC-Stats => Random Data=>

lower bound: 1 and upper bound: 2500. Set start row to 1 and stop row at 40

• Then click the name tab and set Sort (A) in order to set them as ascending.

(Chart on the following page)




Height of Sample

• The height data collected is out of the sample size (n) of forty


• See Figure 1.1

46 556 168

9

200

3

2321

82 558 177

3

201

9

2346

10

2

590 179

0

210

3

2379

10

8

592 180

9

213

4

2426

30

6

623 181

7

215

6

2485

33

5

1108

8

186

5

217

8

2500

35

6

1093 190

4

219

8

2535

41

0

1643 193

8

222

5

2561

47

8

1678 195

7

225

6

257850 62 64 67 70

54 63 64 67 72

59 63 65 68 72

60 63 66 68 72

60 63 66 68 73

62 63 67 69 75

62 64 67 70 76

62 64 67 70 78




• The histogram is approximately bell-shaped

• Five number summary: Min=50, Q1=63, Med=66, Q3=69, Max=78

• The Summary Statistics (Figure 1.2):

Mean= 65.875, Mode= 63 and 67,

Standard Deviation=5.552

• Range: H-L= 79-52=27

Weight of Sample

• The weight data collected is out of the

sample size (n) of forty


• See figure 2.1

• The histogram is skewed right

•Five Number Summary: Min= 77, Q1=150, Med=172, Q3=215, Max=310

• Summary Statistics: Mean= 180.325, Mode= 185, Standard Deviation=55.517

• Range: H-L= 310-77= 233

Showing of Work

Fig. 16.1 Question 1a

77 11

4

15

0

15

4

17

0

18

5

22

0

260

90 11

4

15

0

15

5

17

5

19

0

22

0

270

11

0

13

0

15

0

15

9

18

0

20

0

23

5

285

11

3

14

0

15

3

16

0

18

5

20

0

24

0

295

11

4

14

5

15

4

16

0

18

5

21

5

24

0

310




Fig. 16.2 Question 1b

Fig. 16.3 Question 3





Fig. 16.5 Question 3b




Fig. 16.6 Question 3c









16.10 Question 6

Documents

Phase III Completed