You didn't mention which column represent temperature and which
is sales.
I assume first one is temperature and other one is sale.
I used excel for calculation purpose.
output is as follows:
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| SUMMARY
OUTPUT |
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Regression Statistics |
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Multiple R |
0.922351 |
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R Square |
0.850732 |
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Adjusted R Square |
0.842876 |
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| Standard
Error |
1041.057 |
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Observations |
21 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
1.17E+08 |
1.17E+08 |
108.2876 |
2.7611E-09 |
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Residual |
19 |
20592210 |
1083801 |
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Total |
20 |
1.38E+08 |
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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 |
-32511.2 |
3408.723 |
-9.53766 |
1.12E-08 |
-39645.78693 |
-25376.7 |
-39645.8 |
-25376.7 |
| X
Variable 1 |
408.6026 |
39.26555 |
10.40613 |
2.76E-09 |
326.4188809 |
490.7864 |
326.4189 |
490.7864 |
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Highlighted column gives multiple R, R square, & Adjusted R
square.
Since calculated value of f is greater than significant f.
We conclude that regression is significant. that is we can
accept the result.
If we increase temperature by 1 sales will increased by
408.606
