Sports scientists want to use nuclear magnetic resonance spectroscopy, NMR, to predict the muscle fibre composition in the thighs of athletes. They obtained the data in the screenshot, which contains three variables: FTF – the percentage of fast twitch fibres in the muscle. T1 – the T1 relaxation time measured in ms. T2 – the T2 relaxation time measured in ms. (a) Perform a linear regression to determine the equation allowing FTF to be predicted by T1, i.e. FTF = b0 + b1T1. i) What is the equation of the best-fit line? ii) What is the F statistic and P value for the regression? Do these indicate that the regression is significant? iii) What is the value of R2? How much variation does the regression take account of?
Sports scientists want to use nuclear magnetic resonance spectroscopy, NMR, to predict the muscle fibre composition in the thighs of athletes. They obtained the data in the screenshot, which contains three variables: FTF – the percentage of fast twitch fibres in the muscle. T1 – the T1 relaxation time measured in ms. T2 – the T2 relaxation time measured in ms. (a) Perform a linear regression to determine the equation allowing FTF to be predicted by T1, i.e. FTF = b0 + b1T1. i) What is the equation of the best-fit line? ii) What is the F statistic and P value for the regression? Do these indicate that the regression is significant? iii) What is the value of R2? How much variation does the regression take account of?
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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Sports scientists want to use nuclear magnetic resonance spectroscopy, NMR, to predict the muscle fibre composition in the thighs of athletes. They obtained the data in the screenshot, which contains three variables:
- FTF – the percentage of fast twitch fibres in the muscle.
- T1 – the T1 relaxation time measured in ms.
- T2 – the T2 relaxation time measured in ms.
(a) Perform a linear regression to determine the equation allowing FTF to be predicted by T1, i.e. FTF = b0 + b1T1.
i) What is the equation of the best-fit line?
ii) What is the F statistic and P value for the regression? Do these indicate that the regression is significant?
iii) What is the value of R2? How much variation does the regression take account of?
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