Research was conducted on the amount of training for 5K and the time a contestant took to run the race. The researcher recorded the number of miles during training ( a 1 month period) and the time to complete the 5K. The results are below. Miles Trained 42 44 78 12 56 15 Time (Minutes) 34.2 24.7 27.1 29.9 19.8 27.8a) Give the correlation coefficient. r = b) Give the equation of the regression line. Round the values to 4 deimal places. This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box. y = x + c) Interpret the y-intercept (Explain it's meaning, do not just give its value.)
Research was conducted on the amount of training for 5K and the time a contestant took to run the race. The researcher recorded the number of miles during training ( a 1 month period) and the time to complete the 5K. The results are below. Miles Trained 42 44 78 12 56 15 Time (Minutes) 34.2 24.7 27.1 29.9 19.8 27.8a) Give the correlation coefficient. r = b) Give the equation of the regression line. Round the values to 4 deimal places. This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box. y = x + c) Interpret the y-intercept (Explain it's meaning, do not just give its value.)
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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Research was conducted on the amount of training for 5K and the time a contestant took to run the race. The researcher recorded the number of miles during training ( a 1 month period) and the time to complete the 5K. The results are below.
a) Give the correlation coefficient .
r =
b) Give the equation of the regression line. Round the values to 4 deimal places.
This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box.
y = x +
c) Interpret the y-intercept
(Explain it's meaning, do not just give its value.)
d) Predict the time in the 5K if someone trained 78 miles.
Use the rounded values entered for the slope and intercept of the regression line to compute the predicted y-value.
y =
e) Give the residual for 78 miles trained.
This is the actual y value for the runner who trained for miles minus the predicted value.
Residual=
Miles Trained | 42 | 44 | 78 | 12 | 56 | 15 |
Time (Minutes) | 34.2 | 24.7 | 27.1 | 29.9 | 19.8 | 27.8 |
r =
b) Give the equation of the regression line. Round the values to 4 deimal places.
This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box.
y = x +
c) Interpret the y-intercept
(Explain it's meaning, do not just give its value.)
d) Predict the time in the 5K if someone trained 78 miles.
Use the rounded values entered for the slope and intercept of the regression line to compute the predicted y-value.
y =
e) Give the residual for 78 miles trained.
This is the actual y value for the runner who trained for miles minus the predicted value.
Residual=
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