Refer to Exercise 11.85. A realtor suspects that square

Chapter 11, Problem 86E

(choose chapter or problem)

Problem 86E

Refer to Exercise 11.85. A realtor suspects that square footage x1 might be the most important predictor variable and that the other variables can be eliminated from the model without much loss in prediction information. The simple linear regression model for selling price versus square footage was fit to the 15 data points that were used in Exercise 11.85, and the realtor observed that SSE = 1553. Can the additional independent variables used to fit the model in Exercise 11.85 be dropped from the model without losing predictive information? Test at the α= .05 significance level.

Reference

A real estate agent’s computer data listed the selling price Y (in thousands of dollars), the living area x1 (in hundreds of square feet), the number of floors x2, number of bedrooms x3, and number of bathrooms x4 for newly listed condominiums. The multiple regression model E(Y ) = β0 + β1 x1 + β2 x2 + β3 x3 + β4 x4 was fit to the data obtained by randomly selecting 15 condos currently on the market.

a If R2 = .942, is there sufficient evidence that at least one of the independent variables contributes significant information for the prediction of selling price?

b If Syy = 16382.2, what is SSE?