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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

FrequencyPercentValid PercentCumulative Percent
Valid Male1050.050.0 50.0 
Female1050.050.0 100.0
Total20100.0100.0

Activity level


FrequencyPercentValid PercentCumulative Percent
Valid very active945.045.0 45.0 
active moderate1155.055.0 100.0 
Total20100.0100.0

Importance of exercise

FrequencyPercentValid PercentCumulative Percent
Valid very important 1890.090.090.0
important210.010.0100.0
Total20100.0100.0

How often exercise

FrequencyPercentValid PercentCumulative Percent
Valid once a week 315.015.015.0 
twice a week840.040.055.0
more than three times a week840.0 40.095.0
not at all15.05.0100.0
Total20100.0100.0

Sleeping better after exercise?


FrequencyPercentValid PercentCumulative Percent
Valid yes1995.095.095.0
no15.05.0100.0
Total20100.0100.0

Do you compare yourself to others?


FrequencyPercentValid PercentCumulative Percent
Valid yes210.010.010.0
no1470.070.080.0
sometimes420.020.0100.0
Total20100.0100.0

Satisfaction with your life


FrequencyPercentValid PercentCumulative Percent
Valid very satisfied945.0 45.045.0
satisfied1155.0 55.0100.0
Total20100.0100.0

Define your mental health status


FrequencyPercentValid PercentCumulative Percent
Valid good1050.050.050.0 
poor15.05.055.0
excellent945.045.0100.0 
Total20100.0100.0

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.

IDQuestionLevel of Measurement Central TendencyValue
Question 1What is your age?ScaleMean42.85
Question 2What is your gender?NominalModeFemale, Male (Bi-Modal)
Question 3How active do you consider yourself?OrdinalMedian2 (Active Moderate)
Question 4In your opinion how important is exercise?OrdinalMedian1 (Very Important)
Question 5How often do you exercise a week?OrdinalMedian2 (Twice a week)

Question 6After a session of exercise do you sleep better?Nominal Mode1 (Yes)
Question 7Do you compare yourself to others?Nominal Mode2 (No)
Question 8Are you satisfied with your life?OrdinalMedian2 (Satisfied)
Question 9How you would define your emotional and mental status?OrdinalMedian1.5
Question 10Do you agree exercise helps support emotional and mental health?OrdinalMedian3 (Strongly Agreed)
Recorded AgeAge GroupOrdinalMedian3 (36-45 Years)

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

Age  

N            Valid20
               Missing0
Mean42.85
Median42.00
Mode42a
Std. Deviation9.837
Range38
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 2526-3536-4546-5556 and olderTotal
Activity     level very active022419
active moderate1252111
Total1476220

Chi-Square Tests


ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square2.780a4.595
Likelihood Ratio3.1944.526
Linear-by-Linear Association.8761.349
N of Valid Cases20

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

ValueApprox. Sig.
Nominal by Nominal
 Phi
373.595
Cramer's V373.595
N of Valid Cases20

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 2526-3536-4546-5556 and olderTotal
Importance of exercise       very important 1375218
important010102
Total1476220

Chi-Square Tests


ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square2.780a4.595
Likelihood Ratio3.1944.526
Linear-by-Linear Association.8761.349
N of Valid Cases20

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


ValueApprox. Sig.
Nominal by Nominal
 Phi


.373.595
Cramer's V.373.595
N of Valid Cases20

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 25under 25under 25under 2556 and olderTotal
Importance of exercise very important1375218
important010102
Total1476220

Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square2.407a4.661
Likelihood Ratio3.0984.542
Linear-by-Linear Association.0801.778
N of Valid Cases20

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

Symmetric Measures

ValueApprox. Sig.
Nominal by Nominal       Phi.347.661
Cramer's V.347.661
N of Valid Cases20

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

How often exercise * Age group Crosstabulation
Count  

GenderGender

MaleFemaleTotal
How often exercise once a week033
twice a week448
more than three times a week538
not at all101
Total101020

Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square4.500a3.212
Likelihood Ratio6.0513.109
Linear-by-Linear Association3.7091.054
N of Valid Cases20

a. 8 cells (100.0%) have an expected count of less than 5. The minimum expected count is .50.
Symmetric Measures
ValueApprox. Sig.
Nominal by Nominal Phi .474.212
Cramer's V .474.212
N of Valid Cases20
Decision: We do not reject the null hypothesis

After a session of exercise do you sleep better?
Sleeping better after exercise? * Gender Crosstabulation
Count

GenderGenderTotal

MaleFemale
Sleeping better after exercise? yes91019
no101
Total101020
Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)
Pearson Chi-Square1.053a1.305

Continuity Corrections00011.000

Likelihood Ratio1.4391.230

Fisher's Exact Test


1.000.500
Linear-by-Linear Association1.0001.317

N of Valid Cases20



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

ValueApprox. Sig.
Nominal by Nominal Phi-.229.305
Cramer's V-.229.305
N of Valid Cases20
Decision: We do not reject the null hypothesis
Do you compare yourself to others?
Do you compare yourself to others? * Gender Crosstabulation
Count

GenderGender

MaleFemaleTotal
Do you compare yourself to others?                                     yes112
no8614
sometimes134
Total101020
Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square1.286a2.526
Likelihood Ratio1.3332.513
Linear-by-Linear Association.6551.418
N of Valid Cases20

a. 4 cells (66.7%) have an expected count of less than 5. The minimum expected count is 1.00.
Symmetric Measures

ValueApprox. Sig.
Nominal by Nominal Phi.254.526
Cramer's V.254.526
N of Valid Cases20
Decision: We do not reject the null hypothesis

Are you satisfied with your life?
Satisfaction with your life * Gender Crosstabulation

GenderGender

MaleFemaleTotal
Satisfaction with your life     very satisfied639
satisfied4711
Total101020
Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)
Pearson Chi-Square1.818a1.178

Continuity Correction.8081.369

Likelihood Ratio1.8481.174

Fisher's Exact Test


.370.185
Linear-by-Linear Association1.7271.189

N of Valid Cases20



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

ValueApprox. Sig.
Nominal by Nominal Phi.302.178
Cramer's V.302.178
N of Valid Cases20
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  

GenderGender

MaleFemaleTotal
Define your mental health status good4610
poor101
excellent549
Total101020
Chi-Square Tests


ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square1.511a2.470
Likelihood Ratio1.9002.387
Linear-by-Linear Association.4511.502
N of Valid Cases20

a. 4 cells (66.7%) have an expected count of less than 5. The minimum expected count is .50.

Symmetric Measures

ValueApprox. Sig.
Nominal by Nominal Phi.275.470
Cramer's V.275.470
N of Valid Cases20
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

GenderGender

MaleFemaleTotal
Exercise helps mental health agree369
strongly agree7411
Total101020
Chi-Square Tests

ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)
Pearson Chi-Square1.818a1.178

Continuity Correction.8081.369

Likelihood Ratio1.8481.174

Fisher's Exact Test


.370.185
Linear-by-Linear Association1.7271.189

N of Valid Cases20



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

ValueApprox. Sig.
Nominal by Nominal Phi-.302.178
Cramer's V-.302.178
N of Valid Cases20

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.