www.Pyrczak.com/data use data sets career-a.sav and career-e.sav You are interested in evaluating the effect of gender (sex) and age (agecat4) on respondents’ income (rincom91) while controlling for hours worked per week (hrs1). 1. Develop the appropriate research question and hypotheses for main effects and interaction. 2. Use career-a.sav to screen data for missing data and outliers. What steps, if any, are necessary for reducing missing data and outliers? For all subsequent analyses, use career-e.sav, which eliminates outliers in rincom2. 3. Test the assumptions of normality, homogeneity of regression slopes, and homogeneity of variance. a. What steps, if any, are necessary for increasing normality? b. Do the covariate and factors interact? Can you conclude homogeneity of regression slopes? c. Can you conclude homogeneity of variance? 4. Create a line plot of the factors. Do factors interact? 5. Conduct ANCOVA a. Is factor interaction significant? Explain b. Are main effects significant? Explain. c. Does the covariate significantly influence the DV? d. What can you conclude from the effect size for each main effect? 6. Write a results statement.