Consider the data described in Exercise 9.52 on homes for sale in California and suppose that we are interested in predicting the Size (in thousands of square feet) for such homes.
(a) What is the total variability in the sizes of the 30 homes in this sample? ANOVA with any of the other variables as a predictor.)

(b) Which other variable in the HomesForSaleCA dataset explains the greatest amount of the total variability in home sizes? Explain how you decide on the variable.

(c) How much of the total variability in home sizes is explained by the ‘‘best’’ variable identified in part (b)? Give the answer both as a raw number and as a percentage.

(d) Which of the variables in the dataset is the weakest predictor of home sizes? How much of the variability does it explain?

(e) Is the weakest predictor identified in part (d) still an effective predictor of home sizes? Include some justification for your answer.

Exercise 9.52

The dataset HomesForSaleCA contains a random sample of 30 houses for sale in California. We are interested in whether we can use number of bathrooms Baths to predict number of bedrooms Beds in houses in California.