Please use minitab or Excel to solve it.

Heat treating is often used to carburize metal parts, such as gears. The thickness of the carburized layer is considered a crucial feature of the gear and contributes to the overall reliability of the part. Because of the critical nature of this feature, two different lab tests are performed on each furnace load. One test is run on a sample pin that accompanies each load. The other test is a destructive test, where an actual part is cross-sectioned. This test involves running a carbon analysis on the surface of both the gear pitch (top of the gear tooth) and the gear root (between the gear teeth). Table 12-6 shows the results of the pitch carbon analysis test for The regressors are furnace temperature (TEMP), carbon concentration and duration of the carburizing cycle (SOAKPCT, SOAKTIME), and carbon concentration and duration of the diffuse cycle (DIFFPCT, DIFFTIME).

TABLE IS IN THE ATTACHED FILE

A.Fit a stepwise regression model using all five regressors. Write out the equation. Summarize this analysis by providing the equation, ?², and list the standard errors.What does the analysis of variance indicate?

B. Check for multicollinearity. Explain your findings.

Temp SoakTime SoakPct DiffTime 1650 0.58 1.1 0.25 1650 0.66 1.1 0.33 1650 0.66 1.1 0.33 1650 0.66 1.1 0.33 1600 0.66 1.15 0.33 1600 0.66 1.15 0.33 1650 1 1.1 0.5 1650 1.17 1.1 0.58 1650 1.17 1.1 0.58 1650 1.17 1.1 0.58 1650 1.17 1.1 0.58 1650 1.17 1.1 0.58 1650 1.17 1.15 0.58 1650 1.2 1.15 1.1 1650 2 1.15 1 1650 2 1.1 1.1 1650 2.2 1.1 1.1 1650 2.2 1.1 1.1 1650 2.2 1.15 1.1 1650 2.2 1.1 1.1 1650 2.2 1.1 1.1 1650 2.2 1.1 1.5 1650 3 1.15 1.5 1650 3 1.1 1.5 1650 3 1.1 1.5 1650 3 1.15 1.66 1650 3.33 1.1 1.5 1700 4 1.1 1.5 1650 4 1.1 1.5 1650 4 1.15 1.5 1700 12.5 1 1.5 1700 18.5 1 1.5 DiffPct 0.9 0.9 0.9 0.95 1 1 0.8 0.8 0.8 0.8 0.9 0.9 0.9 0.8 0.8 0.8 0.8 0.8 0.8 0.9 0.9 0.9 0.8 0.7 0.75 0.85 0.8 0.7 0.7 0.85 0.7 0.7 Pitch 0.013 0.016 0.015 0.016 0.015 0.016 0.014 0.021 0.018 0.019 0.021 0.019 0.021 0.025 0.025 0.026 0.024 0.025 0.024 0.025 0.027 0.026 0.029 0.03 0.028 0.032 0.033 0.039 0.04 0.035 0.056 0.068