The data in Questions 1 and 2 come from prqfile-a.sav, which can be downloaded from this Weh site:

www.Pvrczak.com/data

1. The table below presents means for the number of hours worked last week (hrsl) for individuals by general happiness {happy) and job satisfaction (satjob2). Using the data below, draw a line plot. Use the line plot to complete the following steps to estimate the factor main effects on the dependent variable and the interaction between factors.

Very Satisfied with Job Not Very Satisfied with Job

Very happy 43 40

Pretty happy 42 42

Not too happy 38 40

Develop the appropriate hypotheses for main effects and interaction.

Do the factors interact? If so, do you think the interaction will be statistically significant? Explain.

Do you think that there will be a significant main effect for the factor of general happiness? If so, which groups do you think will be significantly different?

Do you think that there will be a significant main effect for the factor of job satisfaction?

2. Using your hypotheses from Question 1, complete a factorial ANOVA analysis and Bonferroni's post hoc test. The variables used were hours worked last week (hrsl), general happiness (happy), and job satisfaction (satjob2). Use the questions below to guide your interpretation of the output.

Is factor interaction significant? Explain.

Are main effects significant? Explain.

1 low do these results compare with your estimation in Question 1 ?

3. Use the salary-a.sav data file and the salary-b.sav data file to determine if current salaries (salnow) are related to gender (sex) and minority status (minority).

a. Develop the appropriate hypotheses for main effects and interaction.

b. Using salary-a.sav, evaluate your data to ensure that they meet the necessary assumptions.

c. Use salary-b.sav, which includes the transformed variable of salnow3, to run the appropriate analyses and interpret your results.

d. Write a results statement.

Exercises for Chapter 5

The exercises below utilize the data sets career-a.sav and career-e.sav, which can be downloaded this Web site:

www.Pyrczak.com/data

You are interested in evaluating the effect of gender (ser) and age (agecat4) on respondents' income (rincom91) while controlling for hours worked per week (hrsl).

Develop the appropriate research questions and/or hypotheses for main effects and interaction.

Use career-a.sav to screen data for missing data and outliers. What steps, if any, are necessary reducing missing data and outliers?

For all subsequent analyses, use career-e.sav, which eliminates outliers in rincom2.

Test the assumptions of normality, homogeneity of regression slopes, and homogeneity of variance.

What steps, if any, are necessary for increasing normality?

Do the covariate and factors interact? Can you conclude homogeneity of regression slopes?

Can you conclude homogeneity of variance?

Create a line plot of the factors. Do factors interact?

Conduct ANCOVA.

Is factor interaction significant? Explain.

Are main effects significant? Explain.

Does the covariate significantly influence the DV? Explain.

What can you conclude from the effect size for each main effect?

Write a results statement.