A trainer collected the data in the following table for a random sample of 30 contestants in
Question:
A trainer collected the data in the following table for a random sample of 30 contestants in the Hilly Hundred (mile) bike race in Bloomington Indiana. He wants to use this information to predict times (in minutes) to complete the Hilly Hundred race. The trainer believes that the time to complete the race is affected by the age of the racer. This data is given below.
Age | Time | | Age | Time |
30 | 335 | | 20 | 505 |
26 | 335 | | 25 | 515 |
32 | 345 | | 20 | 525 |
28 | 350 | | 21 | 550 |
25 | 350 | | 16 | 575 |
25 | 375 | | 38 | 595 |
22 | 380 | | 18 | 605 |
25 | 400 | | 20 | 615 |
23 | 400 | | 36 | 645 |
25 | 410 | | 16 | 680 |
35 | 430 | | 39 | 730 |
20 | 435 | | 40 | 785 |
18 | 460 | | 41 | 810 |
34 | 485 | | 14 | 875 |
31 | 500 | | 12 | 880 |
Create a scatter plot for these data. Comment on the observed relationship between Y and X.
Estimate an appropriate regression equation to predict the time to complete the race. Interpret the estimated regression coefficients.
Analyze the residual versus fit plot. Does this plot suggest that the regression equation is adequate? If not fit an alternative model until the results are satisfactory.
Use your final regression equation to predict the time to complete the race for a 31 year old runner.
Applied Regression Analysis and Other Multivariable Methods
ISBN: 978-1285051086
5th edition
Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Eli S. Rosenberg