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 |
0.645566 |
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Square |
0.416756 |
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Adjusted R Square |
0.287146 |
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Standard Error |
14.26945 |
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Observations |
12 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
2 |
1309.446 |
654.7232 |
3.215463 |
0.088375 |
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Residual |
9 |
1832.554 |
203.6171 |
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Total |
11 |
3142 |
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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 |
67.90951 |
17.56506 |
3.866171 |
0.003811 |
28.17459 |
107.6444 |
28.17459 |
107.6444 |
| X1 |
0.402109 |
0.214897 |
1.871172 |
0.094123 |
-0.08402 |
0.888239 |
-0.08402 |
0.888239 |
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X2 |
-0.57943 |
0.315883 |
-1.83431 |
0.099811 |
-1.294 |
0.13515 |
-1.294 |
0.13515 |
R2=0.4168
F=3.2155
P-value for overall model =0.0884
t1=1.8712
for b1, P-value =0.0941
t2= -1.8343
for b2, P-value =0.0998
- The overall regression model is not statistically
significant at α=0.05
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neither regression coefficient is statistically
significant
