Output using excel:
SUMMARY OUTPUT |
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Regression Statistics |
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Multiple
R |
0.423071 |
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R
Square |
0.178989 |
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Adjusted
R Square |
0.1425 |
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Standard
Error |
6.964542 |
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Observations |
48 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
2 |
475.8568 |
237.9284 |
4.90525 |
0.011826 |
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Residual |
45 |
2182.718 |
48.50485 |
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Total |
47 |
2658.575 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
Intercept |
7.061791 |
2.964789 |
2.381886 |
0.021513 |
1.090399 |
13.03318 |
1.090399 |
13.03318 |
RBI's |
0.110976 |
0.068915 |
1.610321 |
0.114321 |
-0.02783 |
0.249778 |
-0.02783 |
0.249778 |
HR's |
0.03709 |
0.186675 |
0.198688 |
0.843401 |
-0.33889 |
0.413074 |
-0.33889 |
0.413074 |
a) Regression equation:
y? = 7.0618 + 0.1110 x1 + 0.0371 x2
b) Predicted salary for RBI = 31 and HR = 20
y? = 7.0618 + 0.1110 * 31 + 0.0371 *20 = 11.2
millions of dollars
c) Answer: For each RBI, a baseball player's
predicted salary increases by 0.111 million dollars.
d) Answer: For each HR, a baseball player's
predicted salary increases by 0.0371 million dollars.