# Question

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.

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 = β0 + β1.

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 = β0 + β1.

## Answer to relevant Questions

Refer to the data of Exercise 11.22. a. Estimate σ2e. b. Estimate the standard error of β1. c. Place a 95% confidence interval on β1. d. Test the hypothesis that there is a linear relationship between the amount of time ...Refer to Exercise 11.27. a. Test the hypothesis H0: β0 = 0 using a t test with a = .05. b. Determine the p- value for this test, and interpret its value. In exercise Refer to Exercise 11.27. a. Predict the mean total direct cost for all bumper sticker orders with a print run of 2,000 stickers (that is, with RunSize = 2.0). b. Compute a 95% confidence interval for this mean. In exercise Refer to Exercise 11.40. Conduct a test for lack of fit of the linear regression model. In exercise Refer to the Exercise 11.4. a. Use the least- squares prediction equation to predict y when x = 100. b. Comment on the validity of this prediction. In exercise 11.4Post your question

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