Data on 18 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. Ski = 89 – 1.7 · Treadmill Coefficients Estimate Std. Error (Intercept) 89 0.79 Treadmill -1.7 0.82 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? (a). The test statistic is |(use four decimal places) (b). The p-value is (use two decimal places) (c). At the 10% significance level, we Select an answer v the null hypothesis and conclude that there is Select an answer v evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance.
Data on 18 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were measured in minutes and a regression analysis was performed. Ski = 89 – 1.7 · Treadmill Coefficients Estimate Std. Error (Intercept) 89 0.79 Treadmill -1.7 0.82 Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance? (a). The test statistic is |(use four decimal places) (b). The p-value is (use two decimal places) (c). At the 10% significance level, we Select an answer v the null hypothesis and conclude that there is Select an answer v evidence to conclude that there is a linear relationship between cardiovascular fitness and ski race performance.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Problem 1P
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Question
7
![Data on 18 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by
time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were
measured in minutes and a regression analysis was performed.
Ski = 89 – 1.7 · Treadmill
Coefficients Estimate Std. Error
(Intercept)
89
0.79
Treadmill
-1.7
0.82
Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness
and ski race performance?
(a). The test statistic is
(use four decimal places)
(b). The p-value is
(use two decimal places)
(c). At the 10% significance level, we Select an answer v the null hypothesis and conclude that there is
Select an answer v evidence to conclude that there is a linear relationship between cardiovascular fitness
and ski race performance.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F65849a41-4482-4769-855f-5d56c79ad494%2F59bb3d84-90fd-45c3-a508-b7713c1fc792%2Fysv7vwn_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Data on 18 randomly selected athletes was obtained concerning their cardiovascular fitness (measured by
time to exhaustion running on a treadmill) and performance in a 20-km ski race. Both variables were
measured in minutes and a regression analysis was performed.
Ski = 89 – 1.7 · Treadmill
Coefficients Estimate Std. Error
(Intercept)
89
0.79
Treadmill
-1.7
0.82
Is there sufficient evidence to conclude that there is a linear relationship between cardiovascular fitness
and ski race performance?
(a). The test statistic is
(use four decimal places)
(b). The p-value is
(use two decimal places)
(c). At the 10% significance level, we Select an answer v the null hypothesis and conclude that there is
Select an answer v evidence to conclude that there is a linear relationship between cardiovascular fitness
and ski race performance.
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