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A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model E(y) = Bo + B1x. Using the method of least squares, the faculty group obtained the following prediction equation: y = 14,000 - 2,000x Interpret the estimated slope of the line. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. O For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000. O For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points.

A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model E(y) = Bo + B1x. Using the method of least squares, the faculty group obtained the following prediction equation: y = 14,000 - 2,000x Interpret the estimated slope of the line. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. O For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000. O For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points.

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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Solve the problem. Is there a relationship between the raises administrators at State University receive and their performance on the job? A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model E(y) = Bo + B1x. Using the method of least squares, the faculty group obtained the following prediction equation: y = 14,000 - 2,000x Interpret the estimated slope of the line. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. O For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000. O For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points.
Transcribed Image Text:Solve the problem. Is there a relationship between the raises administrators at State University receive and their performance on the job? A faculty group wants to determine whether job rating (x) is a useful linear predictor of raise (y). Consequently, the group considered the straight-line regression model E(y) = Bo + B1x. Using the method of least squares, the faculty group obtained the following prediction equation: y = 14,000 - 2,000x Interpret the estimated slope of the line. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to decrease $2,000. O For a 1-point increase in an administrator's rating, we estimate the administrator's raise to increase $2,000. O For an administrator with a rating of 1.0, we estimate his/her raise to be $2,000. O For a $1 increase in an administrator's raise, we estimate the administrator's rating to decrease 2,000 points.
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