10.5 A regression was run using a data set of U.S. colleges from years gone by. The variable Public is a dummy (indicator) variable for whether the college is public. In-state tuition is in dollars ($). Answer these questions using the output of the regressions that follow. Model Summary Model R R-Squared Adjusted Sid. Error of the R-Squared Estimate .890 .792 .788 $1,731.909 a. Predictors: (Constant), Average verbal SAT score, Public, Percentage of faculty with PhD degreesCoefficients* Model Unstandardized Coefficients Standardized Sig. Coefficients B Std. Error Beta (Constant) -5147.936 1040.970 -4.945 .000 Percentage of faculty with 22.988 10.377 .109 2.215 .028 PhD degrees Public -5339.047 324.613 -.659 -16.447 .000 Average verbal SAT score 22.183 2.692 -415 8.241 .000 a. Dependent Variable: In-state Tuitiona. Interpret the R-squared and adjusted R-squared. b. Interpret the constant. Do you think that it has an out-of-sample prediction issue? c. Interpret the coefficient of Percentage of faculty with PhD degrees. Is it statistically significant? State the null and alternative hypotheses. Is it practically significant? d. Interpret the coefficient of Public. Is it statistically significant? State the null and alternative hypotheses. Is it practically significant