1. Shown is a partial computer output from a regression analysis Sales Ad NumEmp Temp 11 32 13 40 14 50 10 29 12 23 12 36 15 52 18 52 17 52 60 The regression equation is Sales = 5.20 + 1.25 Ad + 1.5 NumEmp + 0.72 Temp Predictor CoeE SE Coef T Constant 5.200 1. 432 3. 62 0 . 016 Ad 1 . 250 0 . 532 2 . 35 0 . 047 NumEmp 1. 500 0 . 811 1 . 85 0 . 102 Temp 0 . 720 1 .125 0 . 64 D . 538 9= -- R-8q = - Analysis of Variance Source DE MS F P Regression 60.00 0.01 Residual Error ---- 1 . 25 Total Stepwise Regression: Sales versus Ad, NumEmp, Temp Backward elimination. Step 1 2 3 Constant 5.200 4.320 3 . 432 Ad 1.250 2.300 T-Value 2.25 2.90 P-Value 0.024 0 . 024 NumEmp 1.500 3.125 3.205 T-Value 1. 85 4.80 9.72 P-Value 0. 152 0.010 0.002 Temp 0.720 T-Value 0 .64 P-Value 0. 657a) Calculate all of the missing entries. b) Using Analysis of Variance table, determine whether there is a significant linear relationship between Y and at least one of the three explanatory variables at 0.05 level of significance.c) At the 0.01 level of significance, and stepwise regression determine whether each explanatory variable makes a significant contribution to the regression model. Based upon these results, indicate the regression model that should be utilized in this