6. An investigator is interested in understanding the relationship, if any, between the house selling price and size of home (square feet), number of bedrooms, and number of bathrooms. Data were collected for 100 houses sold in a large city.

(a) Write an appropriate regression model for this scenario. Use SAS printout to answer the following questions.

(b) Specify appropriate null and alternate hypotheses for testing the adequacy of the overall model. Report values for the F-statistic, degrees of freedom, and p-value, and state the conclusion of this test.

(c) Test the partial effect of number of bathrooms, and interpret.

(d) Write the equation of the least squares regression "line" for this model.

(e) Use the equation in (d) to predict the house selling price for a house of size 2000 square feet, 3 bedrooms, and 2 bathrooms.

(f) Report the R2 value and give an interpretation of this value in the context of the problem.

Number of Observations Read 100 Number of Observations Used 100 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 3 7.117919ELI 2 3726461 1 75.08 $.0001 Error 96 3.033576E1 1 3159974854 Corrected Total 99 1.01515E12 Root MSE 56214 R-Square 0.7012 Dependent Mean 155331 Adj R-Sq D.6918 Coeff Var 36.18959 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > t] Intercept Intercept -27290 28241 -0.97 0.3363 Size 130.43397 11.95115 10.91 4.0001 Beds Beds -14466 10583 -1.37 0.1749 Baths Baths 6890.26655 13540 0.51 0.6120