From the multiple regression model in question-3, test for multicollinearity between the independent variables. Show the output. Discuss if there is multicollinearity and explain your reasoning ?

3. Develop an estimated multiple linear regression model (Analyze/Regression/Linear) that could be used to predict the alumni giving rate using Graduation Rate, % of Classes under 20, and Student/ Faculty Ratio as independent variables (20 points): a) Show the output. What is the estimated regression equation? What are the slopes and the y-intercept? Office Online Frame Descriptive Statistics a. rredictors: (constant), student-r acuty kato, Graquaton Rate, % of Classes Under 20 ANOVA a a. Dependent Variable: Alumni Giving Rate b. Predictors: (Constant), Student-Faculty Ratio, Graduation Rate, % of Classes Under 20 Confficientc a - Estimated Regression Equation: Alumni Giving Rate: 20.720+.748 x1 + .029 x2 - 1.192 x3 b) What is the coefficient of determination? Interpret it in the current context. The coefficient of determination is .700. With this coefficient, this shows that 70.0% of variance in alumni giving rate is explained by the graduate rate