This exercise utilizes the data set profile-a.sav and profile-b.sav 1. You are interested in examining whether the variables shown here in brackets [years of age (age), hours worked per week (hrs1), years of education (educ), years of education for mother (maeduc), and years of education for father (paeduc)] are predictors of individual income (rimcmdo)). Complete the following steps to conduct this analysis: a. Using profile-a.sav, conduct a preliminary regression to calculate Mahalanobis distance. Identify the critical value for chi-square. Conduct Explore to identify outliers. Which cases should be removed from further analysis? For all subsequent analyses, use profile-b.sav. Make sure that only cases where MAH_1 s 22.458 are selected. b. Create a scatterplot matrix. Can you assume linearity and normality? c. Conduct a preliminary regression to create a residual plot. Can you assume normality and homoscedasticity? d. Conduct multiple regression using the Enter method. Evaluate the tolerance statistics. Is multicollinearity a problem? e. Does the model significantly predict rincmdo/? Explain. f. Which variables significantly predict rincmdo/? Which variable is the best predictor of the DV