Question

9. The following output is taken from applying a variable selection procedure to fit a regression model to predict Y (Earnings) using Scoring Avg., Greens in Reg., Putting Avg. and Sand Saves. (consider a to remove = 0.05, a to enter = 0.05) Regression Analysis: Earnings Scoring Avg., Greens in Reg., Putting Avg. and Sand Saves Candidate terms: Scoring Avg., Greens in Reg., Putting Avg., Sand Saves 1 ---- P -----Step 3 ---- P ----Step Coef 19835 -248 4326 -2795 1767 -----Step 2 ---- Coef 22252 -344.9 0.001 3726 0.092 Coef P Constant Scoring Avg. Greens in Reg. Putting Avg. Sand Saves 31737 - 440.3 0.000 0.050 0.056 0.211 0.007 1622 0.012 1507 0.022 R-sg R-sq(adj) R-sq (pred) Mallows' Cp 250.178 70.268 65.50% 40.918 5.00 253.259 68.30% 64.648 44.938 4.64 262.749 64.57% 61.94% 39.06% 5.78 a) What is the variable selection procedure used in fitting this model? a. Stepwise regression b. Backward elimination c. Forward selection d. Best subset regression b) What variables should be included in the model from the above variable selection procedure? c) According to this output, write down the estimated regression equation to predict Earnings.

Answer 1

a= Step wise Regression Method

because the Model is built in 3 Steps

b= Scoring Average And Sand Saves must be included in the model because there p values are significant.i.e.

P values are less than level of Significance.

Means this variable are significantly effect on the dependent Variable.

c=Estimated regression equation is,

earning = 31737 - 440.3 * Scoring Avg + 1507 * ( Sand Saves )