using excel>Addin>phstat>multiple sample test
>Regression
we have
| Simple Linear Regression Analysis |
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| Regression Statistics |
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| Multiple R |
0.5884 |
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| R Square |
0.3462 |
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| Adjusted R Square |
0.1283 |
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| Standard Error |
3.7695 |
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| Observations |
5 |
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| ANOVA |
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df |
SS |
MS |
F |
Significance F |
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| Regression |
1 |
22.5723 |
22.5723 |
1.5886 |
0.2966 |
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| Residual |
3 |
42.6277 |
14.2092 |
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| Total |
4 |
65.2000 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
| Intercept |
-0.7553 |
5.3167 |
-0.1421 |
0.8960 |
-17.6754 |
16.1648 |
| x |
1.0957 |
0.8694 |
1.2604 |
0.2966 |
-1.6710 |
3.8625 |
| Confidence Interval Estimate |
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| Data |
| X Value |
6 |
| Confidence Level |
99% |
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| Intermediate Calculations |
| Sample Size |
5 |
| Degrees of Freedom |
3 |
| t Value |
5.840909 |
| XBar, Sample Mean of X |
5.8 |
| Sum of Squared Differences from XBar |
18.8 |
| Standard Error of the Estimate |
3.769512 |
| h Statistic |
0.202128 |
| Predicted Y (YHat) |
5.819149 |
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| For Average Y |
| Interval Half Width |
9.8987 |
| Confidence Interval Lower Limit |
-4.0796 |
| Confidence Interval Upper Limit |
15.71786 |
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| For Individual Response Y |
| Interval Half Width |
24.1402 |
| Prediction Interval Lower Limit |
-18.3211 |
| Prediction Interval Upper Limit |
29.95935 |
a )the 0.99 confidence interval for the mean predicted when
x = 6 is (-4.0796 ,15.71786)
b ) the 0.99 prediction interval for an individual predicted
when x = 6. is (-18.3211 ,29.95935)
