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# Correlation and regression analysis in SPSS

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#### Solution Summary

Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.

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## SPSS Exercise: Correlation, Regression, Discriminant analysis

See attached file.

SPSS Exercise Questions
If you know how to operate SPSS, the assignment is fairly simple. The instructions are long, because I have included the scenarios as well. All datasets will be automatically entered into the SPSS by access the link below. I just need the measures ran and a synopsis to show class.

Please go to the website: http://www.prenhall.com/greensalkind [click link, open with Internet Explorer, then click on GreenSalkin], and each bullet point correspond to the Lesson in parentheses. Please copy and paste results & comments (if noted to) MS Word.

- Exercises Correlation (found on website under Lesson 31 Exercise File 2)
Hypothesis: Excellent students tend to do exceptionally well in all subjects, good students tend to do well in all subjects; mediocre students tend to do mediocre on all subjects and so on.

1. Conduct a co-relational analysis to investigate the relationship of the GPA in Math and Science with studentsâ?? GPA in English and History
2. What should Fred conclude from the correlations between the two sets of variables?

- Exercises, Bivariate and partial correlations (Lesson 32 Exercise File 2)
Scenario: A local newspaper reports that the number of violent crimes committed in a region is strongly related to the amount of beer drunk in the region. Susan, a sociologist interested in crime prevention elects to investigate this relationship. She decides that the relationship between beer drinking and violent crimes is spurious and that a third variable, air temperature, could explain this relationship. She collects data on the amount of beer purchased (in hundreds of gallons), the number of violent crimes committed, and the average daily high temperatures for the month of July in 30 U.S. cities.

3. What is the bivariate correlation between amount of beer purchased and violent crimes?
4. What is the partial correlation between amount of beer purchased and violent crimes, holding temperature constant?
5. What should Susan conclude about the relationship between amount of beer purchased and the number of violent crimes committed?
6. Write a Results section based on your analyses. Please be sure to include a graphical display of your data.

- Exercises, Regression (Lesson 33 Exercise File 2)
Scenario Betsy is interested in determining whether the number of publications by a professor can be predicted from work ethic. She has access to a sample of 50 social science professor who were teaching at the same university for a 10-year period. Betsy has collected data on the number of publications each professor has (num_pubs). She also has scores that reflect professors' work ethic (work_eth). These scores range from 1 to 50, with 50 indicating a very strong work ethic.

7. Conduct a bivariate linear regression to evaluate Betsy's research question. From the output, identify the following:
a. Significance test to assess the predictability to number of publications from work ethic
b. Regression Equation
c. Correlation between number of publications and work ethic
8. Create a Scatterplot of the predicted and residual scores. What does this graph tell you about your analyses?
9. Write a Results section based on your analyses.

- Exercises, Discriminant analysis (Lesson 35, Exercise File 2)
Scenario; Jacki is interested in differentiating successful women basketball coaches into three categories: successful coaches as character builders, successful winning coaches, and successful winning coaches and character builders. Based on interview data, she is able to differentiate reliably 100 successful women coaches into these three categories. She collects a series of measures for each coach: average number of points per game over last five years, number of ranked players recruited from high schools for the last five years, a measure of problem â?" focused coping, a rating of likability by the time, a measure of social support offered by the coach, a measure of coach persistence, and a measure of reflecting the continuum of authoritative - authoritarian disciple styles. The SPSS file contains 100 cases, seven predictors, and the grouping variable.

10. Conduct a discriminant analysis. Determine whether both discriminant functions should be interpreted.
11. Interpret the discriminant function or functions.
12. Write a Results section based on your analysis.

- Exercises, Factor analysis, *Note: You may have to Select the "Dimension Reduction" option from the Analyze menu in the software (Lesson 36, Exercise File 1).

Scenario: Terrill is interested in assessing how much women value their careers. He develops a 12 item scale, the Saxon Career Values Scale (SCVS). He has 100 college women take the SCVS. All of the items reflect the value women place on having a career versus having a family. Students are asked to response to each on a 4-pint scale, with 0 indicating 'disagree' and 3 indicating â??agree. As show in below:

Variables Definition
Q01 I consider marriage and having a family to be more important than a career.
Q2 To me, marriage and family are as important as having a career.
Q3 I prefer to pursue my career without the distractions of marriage, children, or a household.
Q4 I would rather have a career than a family
Q5 I often think about what type of job I'll have 10 years from now.
Q6. I could be happy without a career
Q7. I don't need to have a career to be fulfilled
Q8. I would leave my career to raise my children
Q9. Having a career would interfere with my family responsibilities
Q11. Planning for and succeeding in a career is one of my primary goals.
Q12. I consider myself to be very career-minded

13. Conduct a factor analysis. How many factors underlie the SCVS based on the Scree plot?
14. How many factors underline the SCVS based on the eigenvalue-greater-than1 criterion?
15. Write a Results section reporting your analyses.

- Exercises, Reliability analysis (Lesson 37 Exercise File 2)
Scenario: Jessica is interested in assessing humor demeaning to others versus self-deprecating humor. She develops a 10- item measure in which some items represent humor demeaning to others (Don Rickles items), while other items reflect self-deprecating humor (Wood Allen items). She administers her measure to 100 college students. Students are asked to respond to each on a 5-point scale with 1 indicating â??disagreeâ? and 5 indicating â??agree.â? Jessica computes a total score by reverse-scaling the Woody Allen items and then summing all 10 items. The variables in the data set are shown below.

Variables Definition
Item01 I like to make fun of others (Don Reckless)
Item02 I make people laugh by making fun of myself (Woody Allen)
Item 03 People find me funny when I make jokes about others. (Don Reckless)
Item 04 I talk about my problems to make people laugh. (Woody Allen)
Item 05 I frequently make others the target of my jokes. (Don Reckless)
Item 06 People find me funny when I tell them about my failings. (Woody Allen)
Item 07 I love to get people to laugh by using sarcasm (Don Rickles)
Item 08 I am funniest when I talk about my own weaknesses. (Woody Allen)
Item 09 I make people laugh by exposing other people's stupidities (Don Rickles)
Item 10 I am funny when I tell others about the dumb things I have done (Woody Allen)

16. Compute a reliability analysis on the total score, using coefficient alpha
17. Conduct the analysis again, this time computing a split-half reliability coefficient
18. Can you justify the method you chose to split the items?
19. Which estimate of reliability is the more appropriate one? And why?
20. Write a Results section based on your analysis.

- Exercises, Item analysis (Lesson 38, Exercise File 2) *Uses same chart as previous problem which is as follows
Variables Definition
Item01 I like to make fun of others (Don Rickles)
Item02 I make people laugh by making fun of myself (Woody Allen)
Item 03 People find me funny when I make jokes about others. (Don Rickles)
Item 04 I talk about my problems to make people laugh. (Woody Allen)
Item 05 I frequently make others the target of my jokes. (Don Rickles)
Item 06 People find me funny when I tell them about my failings. (Woody Allen)
Item 07 I love to get people to laugh by using sarcasm (Don Rickles)
Item 08 I am funniest when I talk about my own weaknesses. (Woody Allen)
Item 09 I make people laugh by exposing other people's stupidities (Don Rickles)
Item 10 I am funny when I tell others about the dumb things I have done (Woody Allen)

21. Conduct an item analysis on this scale for a single dimension. (Note: You will want to reverse-scale either the Woody Allen or Don Rickles items, but not both sets of items.)
22. Conduct the analysis again, this time computer corrected item-total correlations for separate scales: (1) the Don Rickles scale and (2) the Woody Allen scale.
23. Compute correlations between each item and the other scale to assess discriminant vs. validity.
24. Create a table to summarize your items analysis for the Don Rickles and Woody Allen scales
25. Right a Results section based on your analyses.

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