Using data from the 2012 season for MLB a baseball analytics firm wants to determine which variables are important in predicting a teams wins The data collected in clues wins, earned run average (ERA), and runs scored for the 2012 season The firm also has each team categorized as being in the 0 American league or 1 National league The first thing the firm does is runs a model to predict wins based on ERA and number of runs scored The Summary output is below SUMMARY OUTPUT Regression Statistics Multiple R 0 961591 R Square 0 924658 Adjusted R Square 0 919077 Standard Error 3 394783 Observations 30 ANOVA df SS MS F Significance F Regression 2 3818 837 1909 419 165 6827 6 92E 16 Residual 27 311 1629 11 52455 Total 29 4130 Coefficients Standard Error t Stat P value Intercept 83 04052 9 265717 8 962126 1 41E 09 E R A 19 0864 1 257472 15 1783 9 66E 15 Runs Scored 0 106277 0 010911 9 740068 2 49E 10 What is the regression model equation Group of answer choices Wins 19 08 (ERA) 0 106 (Runs Scored) Wins 19 08 (ERA) 0 106 (Runs Scored) 83 04 19 08 (ERA) 0 106 (Runs Scored) Wins 8 96 15 18 (ERA) 9 74 (Runs Scored)

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Question: Using data from the 2012 season for MLB a baseball analytics firm wants to determine which variables are important in predicting a teams wins. The

Using data from the 2012 season for MLB a baseball analytics firm wants to determine which variables are important in predicting a teams wins. The data collected in clues wins, earned run average (ERA), and runs scored for the 2012 season. The firm also has each team categorized as being in the 0=American league or 1= National league.

The first thing the firm does is runs a model to predict wins based on ERA and number of runs scored. The Summary output is below.

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.961591
R Square	0.924658
Adjusted R Square	0.919077
Standard Error	3.394783
Observations	30

ANOVA
	df	SS	MS	F	Significance F
Regression	2	3818.837	1909.419	165.6827	6.92E-16
Residual	27	311.1629	11.52455
Total	29	4130

	Coefficients	Standard Error	t Stat	P-value
Intercept	83.04052	9.265717	8.962126	1.41E-09
E.R.A.	-19.0864	1.257472	-15.1783	9.66E-15
Runs Scored	0.106277	0.010911	9.740068	2.49E-10

What is the regression model equation

Group of answer choices

Wins = -19.08 (ERA) + 0.106 (Runs Scored)

Wins = -19.08 (ERA) + 0.106 (Runs Scored) + 83.04

-19.08 (ERA) = 0.106 (Runs Scored)

Wins = 8.96 + -15.18 (ERA) + 9.74 (Runs Scored)

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