using excel data analysis tool for regression,steps are: write
data>menu>data>data analysis>regression>enter
required labels>ok> and following o/p is obtained
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.886468 |
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Square |
0.785825 |
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Adjusted R Square |
0.760628 |
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Standard Error |
21.31292 |
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Observations |
20 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
2 |
28332.91 |
14166.46 |
31.18714 |
2.05E-06 |
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Residual |
17 |
7722.086 |
454.2403 |
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Total |
19 |
36055 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
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Intercept |
274.1203 |
37.84651 |
7.242949 |
1.37E-06 |
194.2712 |
353.9695 |
194.2712 |
353.9695 |
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GPA |
98.71444 |
12.54348 |
7.869781 |
4.56E-07 |
72.25001 |
125.1789 |
72.25001 |
125.1789 |
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Gender |
-21.1008 |
10.55492 |
-1.99915 |
0.061839 |
-43.3698 |
1.168104 |
-43.3698 |
1.168104 |
a-1)
MathˆMath^ = 274.12 + 98.71 GPA - 21.10 Female.
a-2)
for female,
MathˆMath^ = 274.12 + 98.71 *3.5 - 21.10 *1 = 598.52
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for male
.MathˆMath^ = 274.12 + 98.71 *3.5 - 21.10 *0 = 619.62
