Please do problem 2, and the problem was given. Please finish the question by using R language.

2. This problem is a slightly altered version of Problem 8.1 from Section 8.6 of the text- book. a Fit the regression model with Tension as response and Sulfur predictor, and pro- duce three diagnostic plots: Residuals vs. Fitted, Scale-Location and a Q Plot. Comment on any violation of the standard linear model assumptions seen in these plots. b) Consider two alternative models given by the predictor transformations 1/Sulfur and log (Sulfur). With Sulfur on the horizontal axis and Tension on the vertical axis, plot these two fitted regressions along with the fit from part a). Note that the two fits from this part will not be linear, since the predictor was transformed Hint: The R function invTranPlot is useful here see Section 8.1 of the R primer c) Replace Sulfur by its logarithm, and consider transforming the response Tension. To do this, find and report the optimal power transformation, ML using the Box Cox procedure discussed in class. Should you transform the variable? Explain. 2. This problem is a slightly altered version of Problem 8.1 from Section 8.6 of the text- book. a Fit the regression model with Tension as response and Sulfur predictor, and pro- duce three diagnostic plots: Residuals vs. Fitted, Scale-Location and a Q Plot. Comment on any violation of the standard linear model assumptions seen in these plots. b) Consider two alternative models given by the predictor transformations 1/Sulfur and log (Sulfur). With Sulfur on the horizontal axis and Tension on the vertical axis, plot these two fitted regressions along with the fit from part a). Note that the two fits from this part will not be linear, since the predictor was transformed Hint: The R function invTranPlot is useful here see Section 8.1 of the R primer c) Replace Sulfur by its logarithm, and consider transforming the response Tension. To do this, find and report the optimal power transformation, ML using the Box Cox procedure discussed in class. Should you transform the variable? Explain