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A company provides maintenance services for home water-filtration systems. The company believes that the number of months since the last maintenance of the system will affect the time needed to service and repair the system. They randomly selected a sample of 19 service calls and recorded the months since last service (M) and the repair time (T) in hours. The summary statistics are as follows: > m = 105 2m2=705 E=75 Σ-37 mt =471 min(M) = 1 max(M) = 10 min(T) = 1 max(T) = 7 n= 19 1. Calculate the absolute value of the strength of the linear relationship between T and M. Round of the final answer to 2 decimal places. 2. Determine the least squares regression equation of T on M and predict repair time in minutes of a water-filtration system that was serviced 6 months ago. Round off all intermediate and final calculations to 2 decimal places. 3. It is statistically valid to predict months since the last maintenance for a repair time value equal to a. TRUE, as this is interpolation b. FALSE, as this is extrapolation c. FALSE, cannot use the model to predict X using

A company provides maintenance services for home water-filtration systems. The company believes that the number of months since the last maintenance of the system will affect the time needed to service and repair the system. They randomly selected a sample of 19 service calls and recorded the months since last service (M) and the repair time (T) in hours. The summary statistics are as follows: > m = 105 2m2=705 E=75 Σ-37 mt =471 min(M) = 1 max(M) = 10 min(T) = 1 max(T) = 7 n= 19 1. Calculate the absolute value of the strength of the linear relationship between T and M. Round of the final answer to 2 decimal places. 2. Determine the least squares regression equation of T on M and predict repair time in minutes of a water-filtration system that was serviced 6 months ago. Round off all intermediate and final calculations to 2 decimal places. 3. It is statistically valid to predict months since the last maintenance for a repair time value equal to a. TRUE, as this is interpolation b. FALSE, as this is extrapolation c. FALSE, cannot use the model to predict X using

MATLAB: An Introduction with Applications
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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A company provides maintenance services for home water-filtration systems. The company believes that the number of months since the last maintenance of the system will affect the time needed to service and repair the system. They randomly selected a sample of 19 service calls and recorded the months since last service (M) and the repair time (T) in hours. The summary statistics are as follows: > m = 105 2m2=705 E=75 Σ-37 mt =471 min(M) = 1 max(M) = 10 min(T) = 1 max(T) = 7 n= 19 1. Calculate the absolute value of the strength of the linear relationship between T and M. Round of the final answer to 2 decimal places. 2. Determine the least squares regression equation of T on M and predict repair time in minutes of a water-filtration system that was serviced 6 months ago. Round off all intermediate and final calculations to 2 decimal places. 3. It is statistically valid to predict months since the last maintenance for a repair time value equal to a. TRUE, as this is interpolation b. FALSE, as this is extrapolation c. FALSE, cannot use the model to predict X using
Transcribed Image Text:A company provides maintenance services for home water-filtration systems. The company believes that the number of months since the last maintenance of the system will affect the time needed to service and repair the system. They randomly selected a sample of 19 service calls and recorded the months since last service (M) and the repair time (T) in hours. The summary statistics are as follows: > m = 105 2m2=705 E=75 Σ-37 mt =471 min(M) = 1 max(M) = 10 min(T) = 1 max(T) = 7 n= 19 1. Calculate the absolute value of the strength of the linear relationship between T and M. Round of the final answer to 2 decimal places. 2. Determine the least squares regression equation of T on M and predict repair time in minutes of a water-filtration system that was serviced 6 months ago. Round off all intermediate and final calculations to 2 decimal places. 3. It is statistically valid to predict months since the last maintenance for a repair time value equal to a. TRUE, as this is interpolation b. FALSE, as this is extrapolation c. FALSE, cannot use the model to predict X using
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