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MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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
Transcribed Image Text:A manufacturing firm has developed a skills test, the scores from which can be used to predict workers' production rating
factors.
1 Click the icon to view the data on the test scores of various workers and their subsequent production ratings.
a. Using POM for Windows' least squares-linear regression module, develop a relationship to forecast production ratings
from test scores. (Round your responses to three decimal places and include a minus sign if necessary.)
Y =
where Y = Production rating and X = Test score.
b. If a worker's test score was 79, what would be your forecast of the worker's production rating?
response as an integer.)
c. Comment on the strength of the relationship between the test scores and production ratings.
The coefficient of correlation for the least-squares regression model is
(Enter your responses rounded to three decimal places.)
There is no
(Enter your
and the coefficient of determination is
relationship. The regression equation explains
% of variation in ratings. (Enter your
response as an integer.)
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