Exercises
1. The following output was generated from conducting a forward multiple regression to identify which IVs {urban, birthrat, Inphone, and Inradio) predict Ingdp. The data analyzed were from the SPSS country-a.sav data file.
a. Evaluate the tolerance statistics. Is multicollinearity a problem?
b. What variables create the model to predict Ingdp? What statistics support your response?
c. Is the model significant in predicting Ingdp? Explain.
d. What percentage of variance in Ingdp is explained by the model?
e. Write the regression equation for Ingdp.
2. This question utilizes the data setsprofile-a.sav andprofile-b.sav, which can be downloaded from this website:
www.Pvrczak.com/data
You are interested in examining whether the variables shown here in brackets [years of age (age), hours worked per week (hrsl), years of education (educ), years of education for mother (imaeduc), and years of education for father (paeduc)] are predictors of individual income (;rincmdol). Complete the following steps to conduct this analysis:
a. Usingprofile-a.sav, conduct a preliminary regression to calculate Mahalanobis distance. Iden¬tify the critical value for chi-square. Conduct Explore to identify outliers. Which cases should be removed from further analysis?
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 rincmdol? Explain.
f. Which variables significantly predict rincmdol? Which variable is the best predictor of the DV?
g. What percentage of variance in rincmdol is explained by the model?
h. Write the regression equation for the standardized variables.
i. Explain why the variables of mother's and father's education are not significant predictors of rincmdol.
Attachment:- Exercises.rar