a) What percent of total variation in FARE does the model overall explain/determine?(0.25 point)b) Does the model overall fit the data? NO YES (CIRCLE ono; 0.25 point)c) Should one interpret the estimated value for the intercept? NO YES (CIRCLE one;(0.25 point)d) Interpret the value for the estimated coefficient for DISTANCE. (0.5 point)e) Which explanatory variable has the least statistically significant relationship with FARE? (0.25 point)f) Predict the FARE (fare price in $s) for an airline ticket with point-to-point DISTANCE of 1000 miles, with 15,000 flown passengers (PAX) on a route, whose passengers fly on SWA, whose passengers fly non-vacation routes, and with market concentration index of 4,500.

6. Use the following MS Excel multiple regression output to complete/ answer Parts a through g: Variables used in this multiple regression model: FARE: response (dependent) variable - average fare price ($) on that route DISTANCE: distance between the two endpoint airports in miles PAX: number of passengers on the route during the period of data collection SWA: whether Southwest Airlines serves that route (Yes) or not (No) VACATION: whether a vacation route (Yes) or not (No); Florida and Las Vegas routes are generally considered vacation routes HI: Herfindahl Index - a measure of market concentration SUMMARY OUTPUT Regression Statistics Multiple R 0.8567 R Square 0.7339 Adjusted R Square 0.7318 Standard Error 39.3716 Observations 538 ANOVA df SS MS F Significance F Regression 5 2701807.711 540361.542 348.5929 5.5794E-179 Residual 632 979676.999 1550.122 Total 637 3681484.709 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 86.67589 7.08935 12.2262 5.2751E-31 72.7544 100.5974 DISTANCE 0.07751 0.00269 28.8351 2.4522E-117 0.0722 0.0828 PAX -0.00011 0.00012 -0.9381 0.3485 -0.0004 0.0001 SWA=YES -61.42324 3.54152 -17.3438 2.0809E-55 68.3778 -54.4687 VACATION=YES -52.21338 3.57526 -14.6041 7.8163E-42 -59.2342 -45.1926 0.00735 0.00099 7.3950 4.5121E-13 0.0054 0.0093 HI