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 32 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 32 miles trained.
This is the actual y value for the runner who trained for miles minus the predicted value.
Residual=
| Miles Trained | 55 | 75 | 32 | 36 | 35 | 22 |
| Time (Minutes) | 25.5 | 23.6 | 20.2 | 24.9 | 27.6 | 31.5 |
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 32 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 32 miles trained.
This is the actual y value for the runner who trained for miles minus the predicted value.
Residual=