1. Longwave (LW) and shortwave (SW) are two appearance measures used in the automotive industry to rate the quality of a paint job. These two measures are generally related. Values for 13 cars are given in lwsw .txt. Use these data to do the following.
(a) Using SW as the independent variable, find the best-fitting line for this set of data.
(b) Calculate SSe.
2. For the data set odor .txt consider using the function (3.3.9) to model the relationship between odor and yellowing. Odor and yellowing are both per formance measures of a monomer used in making optical lenses. Lower values of both are desired. Let Y = odor.
(a) If (30 > 0, what will the sign of Y be? Does this make sense?
(b) If (31 > 0, what is the relationship (increasing, decreasing, etc.) of Y with respect to x? Does this make sense?
(c) Make an appropriate scatter plot for assessing the suitability of this model. (You will have to transform the data.) Comment on your scatter plot. Are there any obvious outliers?
(d) Remove any obvious outliers from your data set, and fit the model to the remaining data points. Report the fitted model.
(e) Explain what (31 represents in the context of the problem.
(f) If a particular monomer has a yellowing value of 6, what is the predicted odor?