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Cardiorespiratory fitness is widely recognized as a major component of overall physical well-being. Direct measurement of maximal oxygen uptake (VO2max) is the single best measure of such fitness, but direct measurement is time-consuming and expensive. It is therefore desirable to have a prediction equation for VO2max in terms of easily obtained quantities. A sample is taken and variables measured are age (years), time necessary to walk 1 mile (mins), and heart rate at the end of the walk (bpm) in addition to the VO2 max uptake. The following output is from a multiple regression. Based on the F-test alone, what is the correct conclusion about the regression slopes?    )  All the regression slopes do not equal zero.   2)  We did not find significant evidence to conclude that at least one slope differs from zero.   3)  At least one of the regression slopes does not equal zero.   4)  All the regression slopes are equal to zero.   5)  We do not have the dataset, therefore, we are unable to make a conclusion about the slopes.

Cardiorespiratory fitness is widely recognized as a major component of overall physical well-being. Direct measurement of maximal oxygen uptake (VO2max) is the single best measure of such fitness, but direct measurement is time-consuming and expensive. It is therefore desirable to have a prediction equation for VO2max in terms of easily obtained quantities. A sample is taken and variables measured are age (years), time necessary to walk 1 mile (mins), and heart rate at the end of the walk (bpm) in addition to the VO2 max uptake. The following output is from a multiple regression. Based on the F-test alone, what is the correct conclusion about the regression slopes?    )  All the regression slopes do not equal zero.   2)  We did not find significant evidence to conclude that at least one slope differs from zero.   3)  At least one of the regression slopes does not equal zero.   4)  All the regression slopes are equal to zero.   5)  We do not have the dataset, therefore, we are unable to make a conclusion about the slopes.

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter13: Probability And Calculus
Section13.3: Special Probability Density Functions
Problem 15E: Describe the standard normal distribution. What are its characteristics?
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Cardiorespiratory fitness is widely recognized as a major component of overall physical well-being. Direct measurement of maximal oxygen uptake (VO2max) is the single best measure of such fitness, but direct measurement is time-consuming and expensive. It is therefore desirable to have a prediction equation for VO2max in terms of easily obtained quantities. A sample is taken and variables measured are age (years), time necessary to walk 1 mile (mins), and heart rate at the end of the walk (bpm) in addition to the VO2 max uptake. The following output is from a multiple regression. Based on the F-test alone, what is the correct conclusion about the regression slopes?   

) 

 All the regression slopes do not equal zero.
 

2) 

 We did not find significant evidence to conclude that at least one slope differs from zero.
 

3) 

 At least one of the regression slopes does not equal zero.
 

4) 

 All the regression slopes are equal to zero.
 

5) 

 We do not have the dataset, therefore, we are unable to make a conclusion about the slopes.
Predictor Constant age HR time s 6.891 Analysis of Variance SOURCE Regression Error Total Coef 17.316 0.078 -0.369 -1.457 Stdev 26.136 0.208 0.226 0.766 R-sq 40.86% DF 3 11 14 SS 360.94 522.36 883.29 t-ratio 0.66 0.37 -1.64 -1.9 MS р R-sq (adj) = 24.73% 120.31 47.49 0.5213 0.715 0.1302 0.08382 F 2.53 р 0.111
Transcribed Image Text:Predictor Constant age HR time s 6.891 Analysis of Variance SOURCE Regression Error Total Coef 17.316 0.078 -0.369 -1.457 Stdev 26.136 0.208 0.226 0.766 R-sq 40.86% DF 3 11 14 SS 360.94 522.36 883.29 t-ratio 0.66 0.37 -1.64 -1.9 MS р R-sq (adj) = 24.73% 120.31 47.49 0.5213 0.715 0.1302 0.08382 F 2.53 р 0.111
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