For 6-12, refer to the attached regression output

For 6-12, refer to the attached regression output. Here we are using years of experience, college GPA, and company entrance score to predict employee salaries at a local firm.

We would conclude that the overall model (using all three explanatory variables) is statistically significant at the .05 level. (2)

1. true
2. false

None of the explanatory variables are useful predictors. (2)

true

false

The most useful predictor in the presence of the other explanatory variables is __________. (2)

Multicollinearity is (3)

severe.

mild.

nonexistent.

Which of the following combinations would be expected to yield the highest pay? Values are years, GPA, and score. (2)

5, 3.7, 80

7, 3.2, 85

8, 3.6, 85

5, 3.8, 85

Regression Output

SUMMARY OUTPUT 1

Regression Statistics
Multiple R	0.686507
R Square	0.4712919
Adjusted R Square	0.3655502
Standard Error	18.962716
Observations	19

ANOVA
	df	SS	MS	F	Significance F
Regression	3	4808.020459	1602.673	4.457014	0.019857133
Residual	15	5393.769015	359.5846
Total	18	10201.78947

	Coefficients	Standard Error	t Stat	P-value
Intercept	-59.69295	38.48117376	-1.55122	0.141687
Years	-0.510186	1.100900645	-0.46343	0.649712
GPA	24.510667	12.31973076	1.989546	0.065194
Score	0.7600061	0.295486746	2.572048	0.021248



	Correlation Matrix

		Salary	Years	GPA	Score
	Salary	1
	Years	0.192517816	1
	GPA	0.484367567	0.280138	1
	Score	0.575980821	0.341399	0.226652	1



SUMMARY OUTPUT 2

Regression Statistics
Multiple R	0.5759808
R Square	0.3317539
Adjusted R Square	0.2924453
Standard Error	20.025434
Observations	19

ANOVA
	df	SS	MS	F	Significance F
Regression	1	3384.483506	3384.484	8.43973	0.009855012
Residual	17	6817.305968	401.018
Total	18	10201.78947

	Coefficients	Standard Error	t Stat	P-value
Intercept	8.103183	18.48029361	0.438477	0.666562
Score	0.8430371	0.290189996	2.905121	0.009855

10 years ago

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For 6-12, refer to the attached regression output

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solution_1.docx