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SUMMARY OUTPUT Regression Statistics Multiple R 0.6700 R Square 0.4489 Adjusted R Square 0.4481 Standard Error 56.4794 Observations 638 ANOVA MS Significance F Regression 1
SUMMARY OUTPUT Regression Statistics Multiple R 0.6700 R Square 0.4489 Adjusted R Square 0.4481 Standard Error 56.4794 Observations 638 ANOVA MS Significance F Regression 1 1652697.391 1652697 39 $18.10041 2.39348-84 Residual 536 2028787.318 3189 91717 Total 637 3681484.709 Coefficients Standard Error E Stor P-up/us Lower 95%% Upper 95% Lower 95.0% Upper 95.0% Intercept 83.9765 4.05 14 20.7277 0.0600 76.0208 91.9323 76.0208 91.9323 DISTANCE 0.0788 0.0035 22.7618 0.0600 D.07 20 0.0856 0.0720 0.0856 a) Write the estimated regression equation. (SHOW WORK 0.25 p/) b) What percent of the total variation in FARE does the regression equation, or DISTANCE, explain or determine? (0.25 point) c) What is the value of the bivariate correlation coefficient between DISTANCE and FARE in the sample? (0.5 point d) Interpret the value for the Standard Error under Regression Statistics in this context (please be specific). (0.5 point) e) Interpret the value for the estimated slope coefficient for DISTANCE in this situation or context (please be specific) (0.5 point) f) Interpret the value for the estimated intercept coefficient in this situation. Should we give any importance to the intercept interpretation? (0.5 point) g) State the hypotheses for assessing the statistical significance of the overall regression equation. (0.5 point) h) Does the model overall fit the data? Use (o = 0.05) (0.5 point) YES NO (CIRCLE one) 1) State the null and the alternative hypotheses to test whether the slope coefficient for DISTANCE is significantly greater than zero. (SHOW WORK: 0.5 p If o - 0.01, determine the critical value for the test statistic associated with the hypotheses in Part 1). (Hint: Note that of = n-p-1) (0.5 point)k) Given the MS Excel output and part ;), state your decision regarding the null hypotheses. SHOW WORK: 0.5 p 1) You are airline analyst. On average, do closer (airport) destinations have significantly LOWER or HIGHER fare prices than father apart (airport) destinations? (0.5 point) m) If the DISTANCE for a pair of airports (A-B) equaled 1550 miles and the DISTANCE for another pair of airports (C-D) equaled 1950 miles, by how much (in ss) do you expect two airline fare prices to differ? (Show zone; 0.5 point)4) The data file Airline_data contains observations for 638 airline flights. The questions below are based this data set. Use the following MIS Excel output, based on a simple regression analysis to answer Parts a) through f). Note that the response variable is price of an airline fare = FARE, $, while the explanatory variable is flight distance in miles = DISTANCE
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