please show Minitab screenshots as well

Transient points of an electronic inverter are influenced by many factors. "data_exam2" is the data on transient point (y, in volts) of PMOS-NMOS inverters and five candidate regressions: x1 = width of the NMOS device, x2 = length of the NMOS device, x3 = with of the PMOS device, x4 = length of the PMOS device, and x5 = temperature. You MUST attach all Minitab outputs that support your answers to receive points. Part 1: Use the whole data set. 1. Fit a multiple linear regression model that uses all regressors to these data. Test the significance of regression using alpha = 0.05. Find the p-value for this test and use it to draw your conclusions. 2. Test the contributions of each variable to the model using t-test with alpha = 0.05. What are your conclusions. 3. Delete x5 from the model. Test the new model for significance of regression. Also test the relative contributions of each variable to the model using t-test. Use alpha = 0.05. What are your conclusions? Part 2: Suppose that you learn that the second observation was recorded incorrectly. Delete this observation for all remaining questions. 4. Refit the model using x1, x2, x3, and x4 as the regressors. Notice that the R2 for this model is considerably higher than the R2 for either of the models fitted previously. Explain why R2 increases. 5. Plot the residuals from the model in Question 4 versus the regressors. Comment on the plots. 6. Use all possible regressions to find the equations that minimizes Cp. 7. Use all possible regressions to find the equations that minimizes MSE. 8. Use stepwise regression to select a subset regression model. Observation Number X1 x2 3 X4 X5 1 3 3 3 3 0 2 8 30 8 8 0 3 3 6 6 6 0 4 4 4 4 12 0 5 8 7 6 5 0 0.787 0.293 1.71 0.203 0.806 4.713 0.607 9.107 9.21 1.365 4.554 6 10 20 5 5 0 7 8 6 3 3 25 8 6 24 4 4 25 9 4 12 4 25 10 12 10 16 8 4 25 11 3 8 10 3 8 3 25 25 12 8 3 0.293 13 3 6 3 50 3 3 14 3 8 8 50 2.252 9.167 0.694 15 4 8 4 8 50 16 2 2 2 50 0.379 5 2 17 2 2 3 50 18 10 15 3 3 50 0.485 3.345 0.208 0.201 19 6 2 3 50 20 6 2 3 75 21 wNow n 4 3 3 75 0.329 22 8 2 2 75 4.966 1.362 23 6 6 4 75 24 w w O 3 8 6 75 1.515 0.751 25 8 8 75