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An air travel service samples domestic airline flights to explore the relationsh

ID: 3266403 • Letter: A

Question

An air travel service samples domestic airline flights to explore the relationship between airfare and distance. The service would like to know if there is a correlation between airfare and flight distance. If there is a correlation, what percentage of the variation in airfare is accounted for by distance? How much does each additional mile add to the fare? The data follow.

Compute the correlation of distance and fare? (Round your answer to 3 decimal places.)

State the decision rule for 0.05 significance level: H0: 0; H1: > 0. (Round your answer to 2 decimal places.)

Compute the value of the test statistic. (Round your answer to 2 decimal places.)

At the 0.05 significance level, is it reasonable to conclude that the correlation coefficient is greater than zero?

What percentage of the variation in Fare is accounted for by Distance of a flight? (Round your answer to the nearest whole number.)

Determine the regression equation. (Round your answers to 5 decimal places.)

How much does each additional mile add to the fare? (Round your answer to 5 decimal places.)

Estimate the fare for a 2,000-mile flight. (Round your answer to 2 decimal places.)

Origin Destination Distance Fare   Detroit, MI   Myrtle Beach, SC 636         $140           Baltimore, MD   Sacramento, CA 2,395         292           Las Vegas, NV   Philadelphia, PA 2,176         303           Sacramento, CA   Seattle, WA 605         267           Atlanta, GA   Orlando, FL 403         239           Boston, MA   Miami, FL 1,258         220           Chicago, IL   Covington, KY 264         151           Columbus, OH   Minneapolis, MN 627         205           Fort Lauderdale, FL   Los Angeles, CA 2,342         180           Chicago, IL   Indianapolis, IN 177         275           Philadelphia, PA   San Francisco, CA 2,521         225           Houston, TX   Raleigh/Durham, NC 1,050         333           Houston, TX   Midland/Odessa, TX 441         170           Cleveland, OH   Dallas/Ft.Worth, TX 1,021         119           Baltimore, MD   Columbus, OH 336         190           Boston, MA   Covington, KY 752         100           Kansas City, MO   San Diego, CA 1,333         132           Milwaukee, WI   Phoenix, AZ 1,460         255           Portland, OR   Washington, DC 2,350         161           Phoenix, AZ   San Jose, CA 621         120           Baltimore, MD   St. Louis, MO 737         331           Houston, TX   Orlando, FL 853         278           Houston, TX   Seattle, WA 1,894         183           Burbank, CA   New York, NY 2,465         343           Atlanta, GA   San Diego, CA 1,891         287           Minneapolis, MN   New York, NY 1,028         127           Atlanta, GA   West Palm Beach, FL 545         141           Kansas City, MO   Seattle, WA 1,489         256           Baltimore, MD   Portland, ME 452         146           New Orleans, LA   Washington, DC 969         127        

Explanation / Answer

First i am pasting the Excel regression output

b1. Correlation r between Fare and distance = 0.314

b2. Here tcritical = 2.0484 so it should be greater than t.

b3. Test Statistic t = 1.748

b4. At the 0.05 significance level, is it reasonable to conclude that the correlation coefficient is greater than zero?

No, as t < tcritical so, it is not reasonable to conclude that the correlation coefficent is not greater than zero.

We shall not reject the null hypothesis.

C. As R2 = 0.0984

so 9.84% of the variation in Fare is accounted for by Distance of a flight.

D1 . The regression equation is

Fare = 173.8052 + 0.030 * Distance.

D2. Each additional mile add $ 0.03 to the fare.

D3. the fare for a 2,000-mile flight.

2000 mile flight fare = 173.8052 + 0.03 * 2000 = $233.8052

SUMMARY OUTPUT Regression Statistics Multiple R 0.313659 R Square 0.098382 Adjusted R Square 0.066181 Standard Error 71.2833 Observations 30 ANOVA df SS MS F Significance F Regression 1 15524.82 15524.82 3.05528 0.091434 Residual 28 142276.6 5081.309 Total 29 157801.5 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 173.8052 24.39283 7.12526 9.41E-08 123.8388 223.7717 123.8388 223.7717 Distance 0.03083 0.017638 1.747936 0.091434 -0.0053 0.066959 -0.0053 0.066959
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