1. Calculate all of the missing entries2. Use the ANOVA table and determine whether there is a significant linear relationship between y and three explanatory variables at 0.05 level of significance.3. At the 0.05 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 problem.

4) Shown is a partial computer output from a regression analysis: X1 X3 10 80 15 87 70 10 65 12 77 8 65 14 78 90 Regression Analysis: y versus x1, x2, x3 . The regression equation is Y X1 - 0. 66 X2 - 0.004 X3 Predictor Coef SE Coef T P Constant 61. 53 26. 10 2.36 0. 057 X1 3. 837 1. 930 1.99 0. 094 -0. 657 1. 508 -0. 44 0. 678 X3 -0. 0035 0. 6235 -0. 01 0. 996 S = 3.777 R-Sq - Analysis of Variance (ANOVA Table) Source DF SS MS P Regression 23.99 0 . 001 Residual Error Total Stepwise Regression: Y versus X1, X2, X3 Backward elimination. Response is Y on 3 predictors, Step 2 Constant 61.53 61 . 42 50.49 X1 3. 84 3 . 84 1. 82 T-Value 1. 99 2. 45 9 . 48 P-Value 0 . 094 0 . 044 . 000 X2 -0. 66 -0. 65 T-Value -0. 44 -0. 66 P-Value 0. 678 0.530 X3 -0. 00 T-Value -0. 01 P-Value 0. 996 S 3. 78 3.50 3.37 R-Sq 92 . 30 92 . 30 91 . 82