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A business statistics professor at State College would iike to deveiob a regression modei to predict the final exam scores for students based on their current GPAs. the number of hours they studied torthe exam' the number of times they were absent during the semester. and their genders. Use the accompanying data to complete parts a through e. E Clickthe icon to ViEW the data. \f\fb. If multicollinearity is present, take the necessary steps to eliminate it. What is necessary to eliminate any multicollinearity? Select all that apply. X A. Remove the independent variable * (GPA). X B. Remove the independent variable x (Hours). X c. Remove the independent variable * (Absences). X D. Remove the independent variable x (Gender). E. Since no multicollinearity is present, no steps are necessary.c. Perform a general stepwise regression using o = 0.10 for the p-value to enter and to remove independent variables from the regression model. Identify the variables to enter into the model. Select all that apply. YA. GPA (X1 ) X B. Absences (X3) LY c. Hours (X2)d. Identify the regression formula for the model in part c. Use X, = GPA, * = Hours, * = Absences, and * = Gender, where * = 1 if the gender is male, and * =0 otherwise. Note that the coefficient is 0 for any variable that was removed or is not significant. y= 50.9 +( 8.3 )xy +( 1.8 )x2 + ( 0 )*g + ( 0 )x4 (Round to one decimal place as needed.)