The LPGA has gathered data on it's golfers and would like to be able topredict earnings for players based on their performance. For each golfer in the LPGA, they have gathered their Earning ($), Scoring Avg., Greens in Reg., and Putting Avg. Sample data is shown below. They have developed 4 different regression models to predict Earning ($) and want to be sure that they only include independent variables in the model that have a coefficient that is not statistically equal to zero using = 0.05. (Specifically that for any of the variables).

Player	Earnings ($)	Scoring Avg.	Greens in Reg.	Putting Avg.
Annika Sorenstam	2,588,240	69.33	0.772	1.75
Paula Creamer	1,531,780	70.98	0.727	1.75
Cristie Kerr	1,360,941	70.86	0.722	1.76
Lorena Ochoa	1,201,786	71.39	0.697	1.75
Jeong Jang	1,131,986	71.17	0.71	1.79
Natalie Gulbis	1,010,154	71.24	0.709	1.78

Based on the Regression Output shown below, which of the 4 models would you select?

Greens in Reg and Putting Avg.

Scoring Avg,Green in Reg.and Putting Avg.

Scoring Avg and Greens in Reg.

Scoring Avg