The two exercises that follow utilize the data sets career-a.sav and career-f.sav, which can be down- loaded from this website:

www.routledge.com/9781138289734

1. You are interested in evaluating the effect of job satisfaction (satjob2) and age category (agecat4) on

the combined DV of hours worked per week (hrs1) and years of education (educ).Use career-a.sav

for steps a and b.

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

b. Screen data for missing data and outliers. What steps, if any, are necessary for reducing missing

data and outliers?

For all subsequent analyses in Question 1, use career-f.sav and the transformed variables of hrs2 and educ2.

c. Test the assumptions of normality and linearity of DVs.

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

ii. Are DVs linearly related?

Conduct MANOVA with post hoc (be sure to test for homogeneity of variance-covariance).

i.Can you conclude homogeneity of variance-covariance? Which test statistic is most appropriate for the interpretation of multivariate results?

ii. Is factor interaction significant? Explain.

iii. Are the main effects significant? Explain.

iv. What can you conclude from univariate ANOVA and post hoc results?

e. Conclude with a results statement.