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11.22 Athletes are constantly seeking measures of the degree of their cardiovascular fitness prior to a major race. Athletes want to know when their training is at a level that will produce a peak performance. One such measure of fitness is the time to exhaustion from running on a treadmill at a specified angle and speed. The important question is then "Does this measure of cardiovascular fitness translate into performance in a 10-km running race?" Twenty experienced distance runners who professed to be at top condition were evaluated on the treadmill and then had their times recorded in a 10-km race. The data are given here Treadmill time (minutes) 7.57.8 7.9 8.1 8.3 8.7 8.9 9.2 949.8 10-km time (minutes) 43.5 45.2 44.9 41.1 43.8 44.4 38.7 43.1 41.8 43.7 Treadmi time (minutes 10.1 10.3 10.5 10.7 10.8 10.9 11.2 11.5 11.7 11.8 10-km time (minutes)39.5 38.2 43.9 37.1 37.7 39.2 35.7 37.2 34.8 38.5 a. Plot the data in a scatterplot. b. Fit a regression model to the data. Does a linear model seem appropriate? c. Obtain the estimated linear regression model y - B B

11.22 Athletes are constantly seeking measures of the degree of their cardiovascular fitness prior to a major race. Athletes want to know when their training is at a level that will produce a peak performance. One such measure of fitness is the time to exhaustion from running on a treadmill at a specified angle and speed. The important question is then "Does this measure of cardiovascular fitness translate into performance in a 10-km running race?" Twenty experienced distance runners who professed to be at top condition were evaluated on the treadmill and then had their times recorded in a 10-km race. The data are given here Treadmill time (minutes) 7.57.8 7.9 8.1 8.3 8.7 8.9 9.2 949.8 10-km time (minutes) 43.5 45.2 44.9 41.1 43.8 44.4 38.7 43.1 41.8 43.7 Treadmi time (minutes 10.1 10.3 10.5 10.7 10.8 10.9 11.2 11.5 11.7 11.8 10-km time (minutes)39.5 38.2 43.9 37.1 37.7 39.2 35.7 37.2 34.8 38.5 a. Plot the data in a scatterplot. b. Fit a regression model to the data. Does a linear model seem appropriate? c. Obtain the estimated linear regression model y - B B

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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11.22 Athletes are constantly seeking measures of the degree of their cardiovascular fitness prior to a major race. Athletes want to know when their training is at a level that will produce a peak performance. One such measure of fitness is the time to exhaustion from running on a treadmill at a specified angle and speed. The important question is then "Does this measure of cardiovascular fitness translate into performance in a 10-km running race?" Twenty experienced distance runners who professed to be at top condition were evaluated on the treadmill and then had their times recorded in a 10-km race. The data are given here Treadmill time (minutes) 7.57.8 7.9 8.1 8.3 8.7 8.9 9.2 949.8 10-km time (minutes) 43.5 45.2 44.9 41.1 43.8 44.4 38.7 43.1 41.8 43.7 Treadmi time (minutes 10.1 10.3 10.5 10.7 10.8 10.9 11.2 11.5 11.7 11.8 10-km time (minutes)39.5 38.2 43.9 37.1 37.7 39.2 35.7 37.2 34.8 38.5 a. Plot the data in a scatterplot. b. Fit a regression model to the data. Does a linear model seem appropriate? c. Obtain the estimated linear regression model y - B B
Transcribed Image Text:11.22 Athletes are constantly seeking measures of the degree of their cardiovascular fitness prior to a major race. Athletes want to know when their training is at a level that will produce a peak performance. One such measure of fitness is the time to exhaustion from running on a treadmill at a specified angle and speed. The important question is then "Does this measure of cardiovascular fitness translate into performance in a 10-km running race?" Twenty experienced distance runners who professed to be at top condition were evaluated on the treadmill and then had their times recorded in a 10-km race. The data are given here Treadmill time (minutes) 7.57.8 7.9 8.1 8.3 8.7 8.9 9.2 949.8 10-km time (minutes) 43.5 45.2 44.9 41.1 43.8 44.4 38.7 43.1 41.8 43.7 Treadmi time (minutes 10.1 10.3 10.5 10.7 10.8 10.9 11.2 11.5 11.7 11.8 10-km time (minutes)39.5 38.2 43.9 37.1 37.7 39.2 35.7 37.2 34.8 38.5 a. Plot the data in a scatterplot. b. Fit a regression model to the data. Does a linear model seem appropriate? c. Obtain the estimated linear regression model y - B B
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