11.36 Use the data from Exercise 11.22.a. Estimate the mean time to run 10 km for athletes having a treadmill time of11 minutes.b. Place a 95% confidence interval on the mean time to run 10 km for athleteshaving a treadmill time of 11 minutes. 11.36Use the data from Exercise 11.22.a. Estimate the mean time to run 10 km for athletes having a treadmill time of11 minutes.b. Place a 95% confidence interval on the mean time to run 10 km for athleteshaving a treadmill time of 11 minutes. 11.9Exercises609treadmill at a specified angle and speed. The important question is then "Does this measure ofcardiovascular fitness translate into performance in a 10-km running race?" Twenty experienceddistance runners who professed to be at top condition were evaluated on the treadmill and thenhad their times recorded in a 10-km race. The data are given here.Treadmill time (minutes)10-km time (minutes)7.57.87.98.18.38.78.99.29.49.843.545.244.941.143.844.438.743.141.843.7Treadmill time (minutes)10-km time (minutes)10.110.310.510.710.810.911.211.511.711.839.538.243.937.137.739.235.737.234.838.5a. 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 ŷ = Bo + ß .

Name: 11.36 Use the data from Exercise 11.22.a. Estimate the mean time to ru
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Description: 11.36 Use the data from Exercise 11.22.a. Estimate the mean time to run 10 km for athletes having a treadmill time of11 minutes.b. Place a 95% confidence interval on the mean time to run 10 km for athleteshaving a treadmill time of 11 minutes. 11.36U

Answered: 1.36 Use the data from Exercise 11.22.…

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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11.36 Use the data from Exercise 11.22.
a. Estimate the mean time to run 10 km for athletes having a treadmill time of
11 minutes.
b. Place a 95% confidence interval on the mean time to run 10 km for athletes
having a treadmill time of 11 minutes.

11.9
Exercises
609
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)
10-km time (minutes)
7.5
7.8
7.9
8.1
8.3
8.7
8.9
9.2
9.4
9.8
43.5
45.2
44.9
41.1
43.8
44.4
38.7
43.1
41.8
43.7
Treadmill time (minutes)
10-km time (minutes)
10.1
10.3
10.5
10.7
10.8
10.9
11.2
11.5
11.7
11.8
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 ŷ = Bo + ß .

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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