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SUMMARY OUTPUT Regression Statistics Multiple R 0.881187818 R 2 0.776491971 Adjusted R 2 0.720614963 Standard Error 14.76589647 Observations 16 ANOVA df SS MS F Significance
SUMMARY OUTPUT
Regression Statistics | |
---|---|
Multiple R | 0.881187818 |
R2 | 0.776491971 |
Adjusted R2 | 0.720614963 |
Standard Error | 14.76589647 |
Observations | 16 |
ANOVA
df | SS | MS | F | Significance F | |
---|---|---|---|---|---|
Regression | 3 | 9089.598993 | 3029.86633 | 13.8964488 | 0.00032868 |
Residual | 12 | 2616.380382 | 218.031699 | ||
Total | 15 | 11705.97938 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
---|---|---|---|---|---|---|
Intercept | 28.84376726 | 174.6652528 | 0.16513741 | 0.87158511 | -351.7191 | 409.40661 |
Avg. Price | -2.123501244 | 0.340389982 | -6.2384364 | 4.3289E-05 | -2.8651473 | -1.3818552 |
Avg. Pricecomp | 1.034560927 | 0.466526637 | 2.21758169 | 0.04664078 | 0.01808671 | 2.05103515 |
Avg. Income | 3.089366053 | 0.998893165 | 3.09278926 | 0.00931394 | 0.91296481 | 5.2657673 |
Question 1 : Use the standard error of the regression to estimate the seat demand range with a 95% confidence interval.
Question 2: Estimate and interpret the own price, cross price and income elasticities of demand.
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