A multiple regression model is to he constructed to predict the nal exam score of a university student doing a particular course based upon their midterm exam score, the average number of hours spent studying per week and the average num her of hours spent watching television per week. Data has been collected on 30 randomly selected individuals: show data a) Find the multiple regression equation using all three explanatory variables. Assume that X1 is midten'n score, X2 is hours studying per week and X3 is hours watching television per week. Give your answers to 3 decimal places. i = \\:| + |:|midterm score + \\:|hows studying + \\:|hows watching television b) At a level of signicance of 0.05, the result of the F test for this model is that the null hypothesis rejected. For parts 1:) and (I), using the data. separately calculate the correlations between the response variable and each of the three explanatory variables c) The explanatory variable that is most correlated with nal score is: 0 mi d-term score 0 hours studying per week 0 hours watching television per week (I) The explanatory variahle that is least correlated with nal score is: 0 mi dterm score 0 hours studying per week 0 hours watching television per week e) The value of R2 for this model, to 2 decimal places, is equal to \\:| D The value of sE for this model, to 3 decimal places, is equal to \\:| 9) Construct a new multiple regression model by removing the van'ahle average hours spent watching refevisfon per week. Give your answers to 3 decimal places. The new regression model equation is: G = \\:| + |:|midterm score + \\:|hows studying h) In the new model oompared to the previous one, the value of R2 {to 2 decimal places) is: 0 increased 0 decreased 0 unchang ed i) In the new model compared to the previous one, the value of sE (to 3 decimal places) is: 0 increased 0 decreased 0 unchang ed