I'm running a regression on chemical prices. The Y (dependent) variable is my price, the X (independent) variables are 6 month rolling average prices for related chemicals.
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When I run this regression, the output is this:
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Please ignore the second regression output, it's not letting me delete the unintentional double-paste.
I can't tell if my confusion is because I'm not fully understanding the concepts statistically, or if there is some procedural reason that excel is giving me these wild values (R square of 1, Adjusted R square of 65535, no F value what so ever, etc...).
Any help would be greatly appreciated. Why does this regression output look so crazy?
Dep Var (Y) | Chem A | Chem B | Chem C | Chem D | Chem E | Chem F | Chem G | Chem H |
1.55 | 1.38 | 2.96 | 1567.08 | 1238.33 | 854.75 | 3.09 | 1133.33 | 0.47 |
1.62 | 1.72 | 3.05 | 1810.00 | 1428.17 | 1404.42 | 3.10 | 1088.54 | 0.57 |
1.54 | 1.72 | 3.15 | 1810.00 | 1448.17 | 1431.71 | 3.19 | 1120.42 | 0.59 |
1.69 | 1.83 | 3.50 | 1985.83 | 1574.33 | 1538.75 | 3.45 | 1312.04 | 0.71 |
1.62 | 1.61 | 2.79 | 1944.17 | 1452.17 | 1465.64 | 2.78 | 1058.13 | 0.68 |
1.70 | 1.67 | 3.21 | 2180.00 | 1469.00 | 1408.00 | 3.26 | 1363.33 | 0.61 |
1.75 | 1.92 | 3.79 | 2132.50 | 1562.00 | 1490.00 | 4.04 | 1481.25 | 0.62 |
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When I run this regression, the output is this:
Regression Statistics | ||||||||
Multiple R | 1 | |||||||
R Square | 1 | |||||||
Adjusted R Square | 65535 | |||||||
Standard Error | ||||||||
Observations | 7 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 8 | 0.037085714 | 0.004635714 | #NUM! | #NUM! | |||
Residual | 65535 | |||||||
Total | 8 | 0.037085714 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -1.28363 | 65535 | #NUM! | -1.283633148 | -1.283633148 | -1.283633148 | -1.283633148 | |
Butane monthly avg | 1.555782 | 65535 | #NUM! | 1.555781703 | 1.555781703 | 1.555781703 | 1.555781703 | |
Toulene monthly avg | 65535 | #NUM! | ||||||
Acryl monthly avg | 0.001087 | 65535 | #NUM! | 0.001086923 | 0.001086923 | 0.001086923 | 0.001086923 | |
LDPE monthly avg | 0.002284 | 65535 | #NUM! | 0.002283682 | 0.002283682 | 0.002283682 | 0.002283682 | |
LLDPE monthly avg | -0.00219 | 65535 | #NUM! | -0.002191373 | -0.002191373 | -0.002191373 | -0.002191373 | |
Mixed xylenes monthly avg | -0.26168 | 65535 | #NUM! | -0.261680247 | -0.261680247 | -0.261680247 | -0.261680247 | |
Para xylene monthly avg | -0.00103 | 65535 | #NUM! | -0.001028792 | -0.001028792 | -0.001028792 | -0.001028792 | |
Propylene chem monthly avg | 65535 | #NUM! |
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Regression Statistics | ||||||||
Multiple R | 1 | |||||||
R Square | 1 | |||||||
Adjusted R Square | 65535 | |||||||
Standard Error | ||||||||
Observations | 7 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 8 | 0.037085714 | 0.004635714 | #NUM! | #NUM! | |||
Residual | 65535 | |||||||
Total | 8 | 0.037085714 | ||||||
Coefficients | Standard Error | t Stat | P -value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -1.28363 | 65535 | #NUM! | -1.283633148 | -1.283633148 | -1.283633148 | -1.283633148 | |
Butane monthly avg | 1.555782 | 65535 | #NUM! | 1.555781703 | 1.555781703 | 1.555781703 | 1.555781703 | |
Toulene monthly avg | 65535 | #NUM! | ||||||
Acryl monthly avg | 0.001087 | 65535 | #NUM! | 0.001086923 | 0.001086923 | 0.001086923 | 0.001086923 | |
LDPE monthly avg | 0.002284 | 65535 | #NUM! | 0.002283682 | 0.002283682 | 0.002283682 | 0.002283682 | |
LLDPE monthly avg | -0.00219 | 65535 | #NUM! | -0.002191373 | -0.002191373 | -0.002191373 | -0.002191373 | |
Mixed xylenes monthly avg | -0.26168 | 65535 | #NUM! | -0.261680247 | -0.261680247 | -0.261680247 | -0.261680247 | |
Para xylene monthly avg | -0.00103 | 65535 | #NUM! | -0.001028792 | -0.001028792 | -0.001028792 | -0.001028792 | |
Propylene chem monthly avg | 65535 | #NUM! |
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Please ignore the second regression output, it's not letting me delete the unintentional double-paste.
I can't tell if my confusion is because I'm not fully understanding the concepts statistically, or if there is some procedural reason that excel is giving me these wild values (R square of 1, Adjusted R square of 65535, no F value what so ever, etc...).
Any help would be greatly appreciated. Why does this regression output look so crazy?