# A Solution to Conduct A Chi Square Test Assignment Using SPSS

## Assignment Instructions

Questionnaire Guidelines – Creation, collection, input & analysis of a research topic.

1. You are required to produce a report based on the results from a questionnaire designed for the purposes of this assignment, keeping it a simple, harmless topic.
2. The questionnaire should be based on a topic of your choice. You must agree on the topic with your workshop tutor BEFORE you actually interview any respondents.
3. The questionnaire should include a title and a brief introductory statement outlining the topic and must be respondent self-completion.
4. Include a minimum of 10 questions in the questionnaire, each of which must count as a variable. One question must be on gender and one on age. Age must be measured in exact years. The remaining variables are dependent variables and should contain a mix of ordinal, nominal, and interval variables.
5. Conduct the questionnaire on no fewer than 20 respondents (e.g. 10 male and 10 female). You should explain the purpose of the questionnaire to each respondent and seek her/his agreement to participate. It is the right of the respondent to refuse your request and under no circumstances must you pressurize them into partaking. Your sample should be friends and family or other students over the age of 18.
6. Gender & age are your I.V. (Independent variables) as you will be comparing male & female, & age responses.
7. Using the “transform” tag create a new variable: age ranges (for example, young (0 - 35), middle-aged (36 – 64), and old (65 upwards).
8. Enter the data from your questionnaire into SPSS and carry out the following

types of analysis on your data set:

• Frequency distribution for each of the variables, including the new age variable.
• The appropriate MCT for each of the variables.
• Mean, standard deviation, median, mode, and range for original age variable.
• Cross tabulation of each of the dependent variables (Row) by gender and age recoded variable (I.V., Column, Manipulated). For each cross-tabulation include both a relevant test of statistical significance (Chi-Square) and a measure of association (phi / Cramer’s V).

9. Create a Questionnaire Results file on a word document.

• The SPSS output presents a table or chart for each of the frequency distributions and the cross-tabulations.
• All tables and charts must be numbered and labeled.
• Each table and chart must have a short interpretative description decoding the results of that table or chart. State what the chart says, means, and or highlights.

## Assignment Solution

#### Statistical Analysis of Benefits of Exercise on Well Being

Introduction

The positive role that physical exercise can play in human well-being and the treatment of a range of medical conditions has received a great deal of attention over recent years, with numerous high-profile reports supporting the popular message that exercise is good for the human body. In addition, research has identified the long-term protection that regular exercise affords against a plethora of somatic complaints, including coronary heart disease, hypertension, a number of cancers, diabetes, and osteoporosis. Unfortunately, while the somatic benefits associated with physical exercise are well documented, hard evidence to support an equivalent relation between exercise and human well-being is less plentiful. The purpose of the present study is therefore to explore the association between gender, age physical exercise frequency, and a number of measures of well-being.

Source of Data

The data used for this study is primary data collected by administering a questionnaire to the respondents. Various questions on age, gender and exercise frequency, and a number of measures of well-being were answered. The data were coded and analyzed using SPSS.

Descriptive Statistics

Frequency Distributions

Gender
 Frequency Percent Valid Percent Cumulative Percent Valid Male 10 50.0 50.0 50.0 Female 10 50.0 50.0 100.0 Total 20 100.0 100.0

Activity level

 Frequency Percent Valid Percent Cumulative Percent Valid very active 9 45.0 45.0 45.0 active moderate 11 55.0 55.0 100.0 Total 20 100.0 100.0

Importance of exercise

 Frequency Percent Valid Percent Cumulative Percent Valid very important 18 90.0 90.0 90.0 important 2 10.0 10.0 100.0 Total 20 100.0 100.0

How often exercise

 Frequency Percent Valid Percent Cumulative Percent Valid once a week 3 15.0 15.0 15.0 twice a week 8 40.0 40.0 55.0 more than three times a week 8 40.0 40.0 95.0 not at all 1 5.0 5.0 100.0 Total 20 100.0 100.0

Sleeping better after exercise?

 Frequency Percent Valid Percent Cumulative Percent Valid yes 19 95.0 95.0 95.0 no 1 5.0 5.0 100.0 Total 20 100.0 100.0

Do you compare yourself to others?

 Frequency Percent Valid Percent Cumulative Percent Valid yes 2 10.0 10.0 10.0 no 14 70.0 70.0 80.0 sometimes 4 20.0 20.0 100.0 Total 20 100.0 100.0

 Frequency Percent Valid Percent Cumulative Percent Valid very satisfied 9 45.0 45.0 45.0 satisfied 11 55.0 55.0 100.0 Total 20 100.0 100.0

 Frequency Percent Valid Percent Cumulative Percent Valid good 10 50.0 50.0 50.0 poor 1 5.0 5.0 55.0 excellent 9 45.0 45.0 100.0 Total 20 100.0 100.0

## The measure of Central Tendency

The table below gives the summary of each question included in the study, their level of measurement, and the appropriate measure of central tendency. The appropriate measure of tendency used for scale measurement is mean, nominal measurement is mode and ordinal measurement is Median.

 ID Question Level of Measurement Central Tendency Value Question 1 What is your age? Scale Mean 42.85 Question 2 What is your gender? Nominal Mode Female, Male (Bi-Modal) Question 3 How active do you consider yourself? Ordinal Median 2 (Active Moderate) Question 4 In your opinion how important is exercise? Ordinal Median 1 (Very Important) Question 5 How often do you exercise a week? Ordinal Median 2 (Twice a week) Question 6 After a session of exercise do you sleep better? Nominal Mode 1 (Yes) Question 7 Do you compare yourself to others? Nominal Mode 2 (No) Question 8 Are you satisfied with your life? Ordinal Median 2 (Satisfied) Question 9 How you would define your emotional and mental status? Ordinal Median 1.5 Question 10 Do you agree exercise helps support emotional and mental health? Ordinal Median 3 (Strongly Agreed) Recorded Age Age Group Ordinal Median 3 (36-45 Years)

The tables below give the descriptive statistics for the age of the participants

Age

 N            Valid 20 Missing 0 Mean 42.85 Median 42.00 Mode 42a Std. Deviation 9.837 Range 38
a. Multiple modes exist. The smallest value is shown
The table above shows that the average age of the respondent is 42.85 with a standard deviation of 9.837. Majority of our 42 years and difference between the maximum and the minimum age was obtain to be 38.
Cross-Tabulation and Chi-Square
The chi-square test of independence is used to determine if there is a significant relationship between two categorical variables. For this analysis, we test for the dependency of the participant's response on each question on Age and gender.
Dependency on Age
The hypothesis and rejection rule are given below;
Null hypothesis: There is no association between the participant's age and their response to the question (i.e they are independent)
Alternative hypothesis: There is an association between the participant's age and their response to the question (i.e they are dependent)
Rejection rule: Reject the null hypothesis if the p-value is less than 0.05
The results for the association between participant age and response to each question are given below;
How active do you consider yourself?

Activity level * Age group Crosstabulation

Count

 Age group under 25 26-35 36-45 46-55 56 and older Total Activity     level very active 0 2 2 4 1 9 active moderate 1 2 5 2 1 11 Total 1 4 7 6 2 20

Chi-Square Tests

 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 2.780a 4 .595 Likelihood Ratio 3.194 4 .526 Linear-by-Linear Association .876 1 .349 N of Valid Cases 20

a. 10 cells (100.0%) have an expected count of less than 5. The minimum expected count is .45.
Symmetric Measures
 Value Approx. Sig. Nominal by Nominal  Phi 373 .595 Cramer's V 373 .595 N of Valid Cases 20

Decision: We do not reject the null hypothesis

In your opinion how important is exercise?

Importance of exercise * Age group Crosstabulation
Count
 Age group under 25 26-35 36-45 46-55 56 and older Total Importance of exercise       very important 1 3 7 5 2 18 important 0 1 0 1 0 2 Total 1 4 7 6 2 20

Chi-Square Tests

 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 2.780a 4 .595 Likelihood Ratio 3.194 4 .526 Linear-by-Linear Association .876 1 .349 N of Valid Cases 20

a. 10 cells (100.0%) have an expected count of less than 5. The minimum expected count is .45.

 Value Approx. Sig. Nominal by Nominal  Phi .373 .595 Cramer's V .373 .595 N of Valid Cases 20

Decision: We do not reject the null hypothesis

In your opinion how important is exercise?

Importance of exercise * Age group Crosstabulation
Count
 Age group under 25 under 25 under 25 under 25 56 and older Total Importance of exercise very important 1 3 7 5 2 18 important 0 1 0 1 0 2 Total 1 4 7 6 2 20

Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 2.407a 4 .661 Likelihood Ratio 3.098 4 .542 Linear-by-Linear Association .080 1 .778 N of Valid Cases 20

a. 8 cells (80.0%) have an expected count of less than 5. The minimum expected count is .10.

Symmetric Measures
 Value Approx. Sig. Nominal by Nominal       Phi .347 .661 Cramer's V .347 .661 N of Valid Cases 20

Decision: We do not reject the null hypothesis
How often do you exercise a week?

How often exercise * Age group Crosstabulation
Count
 Gender Gender Male Female Total How often exercise once a week 0 3 3 twice a week 4 4 8 more than three times a week 5 3 8 not at all 1 0 1 Total 10 10 20

Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 4.500a 3 .212 Likelihood Ratio 6.051 3 .109 Linear-by-Linear Association 3.709 1 .054 N of Valid Cases 20
a. 8 cells (100.0%) have an expected count of less than 5. The minimum expected count is .50.
Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi .474 .212 Cramer's V .474 .212 N of Valid Cases 20
Decision: We do not reject the null hypothesis

After a session of exercise do you sleep better?
Sleeping better after exercise? * Gender Crosstabulation
Count
 Gender Gender Total Male Female Sleeping better after exercise? yes 9 10 19 no 1 0 1 Total 10 10 20
Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 1.053a 1 .305 Continuity Corrections 000 1 1.000 Likelihood Ratio 1.439 1 .230 Fisher's Exact Test 1.000 .500 Linear-by-Linear Association 1.000 1 .317 N of Valid Cases 20
a. 2 cells (50.0%) have an expected count of less than 5. The minimum expected count is .50.
b. Computed only for a 2x2 table

Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi -.229 .305 Cramer's V -.229 .305 N of Valid Cases 20
Decision: We do not reject the null hypothesis
Do you compare yourself to others?
Do you compare yourself to others? * Gender Crosstabulation
Count
 Gender Gender Male Female Total Do you compare yourself to others?                                     yes 1 1 2 no 8 6 14 sometimes 1 3 4 Total 10 10 20
Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 1.286a 2 .526 Likelihood Ratio 1.333 2 .513 Linear-by-Linear Association .655 1 .418 N of Valid Cases 20
a. 4 cells (66.7%) have an expected count of less than 5. The minimum expected count is 1.00.
Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi .254 .526 Cramer's V .254 .526 N of Valid Cases 20
Decision: We do not reject the null hypothesis

Are you satisfied with your life?
Satisfaction with your life * Gender Crosstabulation
 Gender Gender Male Female Total Satisfaction with your life     very satisfied 6 3 9 satisfied 4 7 11 Total 10 10 20
Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 1.818a 1 .178 Continuity Correction .808 1 .369 Likelihood Ratio 1.848 1 .174 Fisher's Exact Test .370 .185 Linear-by-Linear Association 1.727 1 .189 N of Valid Cases 20
a. 2 cells (50.0%) have an expected count of less than 5. The minimum expected count is 4.50.
b. Computed only for a 2x2 table

Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi .302 .178 Cramer's V .302 .178 N of Valid Cases 20
Decision: We do not reject the null hypothesis
How you would define your emotional and mental status?
Define your mental health status * Gender Crosstabulation
Count
 Gender Gender Male Female Total Define your mental health status good 4 6 10 poor 1 0 1 excellent 5 4 9 Total 10 10 20
Chi-Square Tests

 Value df Asymp. Sig. (2-sided) Pearson Chi-Square 1.511a 2 .470 Likelihood Ratio 1.900 2 .387 Linear-by-Linear Association .451 1 .502 N of Valid Cases 20
a. 4 cells (66.7%) have an expected count of less than 5. The minimum expected count is .50.

Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi .275 .470 Cramer's V .275 .470 N of Valid Cases 20
Decision: We do not reject the null hypothesis

Do you agree exercise helps support emotional and mental health?

Exercise helps mental health * Gender Crosstabulation
Count
 Gender Gender Male Female Total Exercise helps mental health agree 3 6 9 strongly agree 7 4 11 Total 10 10 20
Chi-Square Tests
 Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 1.818a 1 .178 Continuity Correction .808 1 .369 Likelihood Ratio 1.848 1 .174 Fisher's Exact Test .370 .185 Linear-by-Linear Association 1.727 1 .189 N of Valid Cases 20
a. 2 cells (50.0%) have an expected count of less than 5. The minimum expected count is 4.50.
b. Computed only for a 2x2 table

Symmetric Measures
 Value Approx. Sig. Nominal by Nominal Phi -.302 .178 Cramer's V -.302 .178 N of Valid Cases 20

Decision: We do not reject the null hypothesis

Conclusion

The study was carried out to investigate the association between gender, age, physical exercise frequency, and a number of measures of well-being. The chi-square test of independence was performed and the results revealed that there is no significant association between the measures of well-being included in the study, age, and gender. That is, the participant's response to each of the questions is independent of their gender and age.