Question

(1 point) Can the cost of flying a commercial airliner be predicted using regression analysis? If so, what variables are related to this cost? A few of many variables that can potentially contribute are type of plane, distance, number of passengers, amount of luggage/freight, weather condition, direction of destination, or even pilot skill. Suppose a study is conducted using only Boeing 737s traveling 800 km on comparable routes during the same season of the year. Can the number of passengers predict the cost of flying such routes? It seems logical that more passengers result in more mass and more baggage, which could, in turn, result in increased fuel consumption and other costs. Suppose the data displayed below are the cost and associated number of passengers for thirty-six 800-km commercial airline flights using Boeing 737s during the same season of the year. We will use these data to develop a regression model to predict cost by number of passengers The data in the .csv file contains the data on the cost and number of passengers of 36 observations (a) Use software to estimate this model. Use three-decimals in each of your least squares estimatesyour answer Cost, Il Number of Passengers, (D) Find the coefficient of determination. Expresses as a percentage, and use two decimal places in your answer. (c) in the context of the data, interpret the meaning of the coefficient of determination A. The percentage found above is the percentage of variation in the cost of flying a 800-km commercial flight using Boeing 737s that can be explained by its linear dependency with the number of passengers B. There is a weak, positive linear relationship between the cost of flying a 800-km commercial flight using Boeing 737s and the number of passengers C. The percentage found above is the percentage of variation in the number of passengers that can be explained by its linear dependency with the cost of flying a 800-km commercial flight using Boeing 737s. D. There is a strong, positive linear relationship between the cost of flying a 800-km commercial flight using Boeing 737s and the number of passengers

Answer 1

EXCEL (Data Analysis) output: SUMMARY OUTPUT Regression Statistics Multiple R 0.844768752 R Square 0.713634245 Adjusted R Square 0.704956495 Standard Error 1.648287321 Observations 35 ANOVA Significance F 1.76604E-10 Regression Residual Total 1 33 34 SS MS F 223.4263425 223.4263 82.23724 89.65608606 2.716851 313.0824286 Intercept Passengers Coefficients - 15.69432024 0.251904507 Standard Error t Stat P-value 2.185314331 -7.18172 3.13E-08 0.027778044 9.068475 1.77E-10 Lower 95% Upper 95% -20.14037565 -11.24826482 0.195389651 0.308419363 The least-squares regression line is Cost =-15.694+0.252 Number of Passengers: -

(b) The value of the coefficient of determination is r2 = 71.36%. A. The percentage found above is the percentage of variation in the cost of flying a 800-km commercial flight using Boeing 737s that can be explained by its linear dependency with the number of passengers. (d) The value of the standard deviation of the regression is S. = 1.648