The accompanying SAS computer output relates to the house price data of Problem 10 in Chapter 8. Use this output and, if necessary, the output associated with Problem 9 in Chapter 9 to answer the following questions.
a. Determine r2Y|X1,X2, the squared multiple correlation between house price (Y) and the independent variables house size (X1) and number of bedrooms (X2).
b. Determine rYX2|X1, the partial correlation of Y with X2 given that X1 is in the model.
c. Determine rYX1|X2, the partial correlation of Y with X1 given that X2 is in the model.
d. Using the t test technique of Problem 2, test H0: ρYX2|X1 = 0. Compare your test statistic value with the partial t test statistic for X2 shown on the SAS output here.
e. Using the t test technique of Problem 2, test H0: ρYX1|X2 = 0. Compare your test statistic value with the partial t test statistic for X1 shown on the SAS output here.
f. Based on your answers to parts (a) through (e), which variables (if any) should be included in the regression model, and what is their order of importance?

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Regression of Y on X1 and X2 ANALYSIS OF VARIANCE Sum of DF Squares Mean Square 2866.86064 F Value Pr>F 20.03 0.0082 Source Model Error Corrected Total 5733.32129 4 572.39300 143082 6 8305,71429 37 R-Square Adj R-Sq 0.9082 Root MSE Dependent Mean Coeff Var 11.96237 105 42857 11.34642 0.8638 PARAMETER ESTIMATES Squared Partial Squared Partial Parametr Standard Variable DF Intercept X1 X2 Error t Value PrCorr Typel Corr Type I 16.09339 24.64694 1.82779 0.65 0.5494 3.13 0.0352 0.09 0.9344 090905 0.00192 0.71014 0.00192 5.72179 11.17315 1338994