$10.00 question 2
- From Mathematics: Statistics
- Closed, but you can still post tutorials
- Due on Oct. 03, 2011
- Asked on Oct 02, 2011 at 7:11:01PM
The following Excel output (see SUMMARY OUTPUT next page) represents regression results from Excel of weekly Crude Oil Prices ($/BBL) on the Gasoline Price (Branded Retail ex all taxes) for California from January 1, 2002 to July 14, 2008.
1-4.Comment specifically on at least 4 of the numbers shown anywhere below.
5. Also, is this a good fit? Why or why not?
6. How much of the variation does this model explain?
7. What’s the correlation coefficient, including its sign?
8. Lately the price of crude oil has decreased from over $145 to less than $90. What decrease in gasoline prices (less taxes) would you expect for every $10 drop in crude oil price given this model?
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SummaryOutput |
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Regression Statistics |
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Multiple R |
0.9466 |
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R Square |
0.8960 |
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AdjustedR Square |
0.8957 |
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Standard Error |
0.2122 |
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Observations |
341 |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
131.6144 |
131.6144 |
2921.8432 |
1.0463E-168 |
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Residual |
339 |
15.2702 |
0.0450 |
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Total |
340 |
146.8846 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
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Intercept |
0.6330 |
0.0259 |
24.4268 |
9.93E-77 |
0.5820 |
0.6840 |
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Crude Oil Cost $/Bbl |
0.0238 |
0.0004 |
54.0541 |
1.05E-168 |
0.0230 |
0.0247 |
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- Posted on Oct. 03, 2011 at 10:57:10AM
regression explantion.doc (25K)