Suppose that a multiple linear regression model was fit to data and that the following output resulted: Coefficients: (Intercept) stop distance mpg weight Estimate 8.63315 -0.06078 -0.03793 0.17295 Std. Error 5.91641 0.07368 0.08661 0.08165 t value 1.459 -0.825 -0.438 2.118 Pr(>|t|) 0.1482 0.4117 0.6626 0.0371 True or False? It is likely that at least one explanatory variable would be left in our model if a backwards selection process were performed. (Our significance level is 0.05 for all testing purposes.) True False
Suppose that a multiple linear regression model was fit to data and that the following output resulted: Coefficients: (Intercept) stop distance mpg weight Estimate 8.63315 -0.06078 -0.03793 0.17295 Std. Error 5.91641 0.07368 0.08661 0.08165 t value 1.459 -0.825 -0.438 2.118 Pr(>|t|) 0.1482 0.4117 0.6626 0.0371 True or False? It is likely that at least one explanatory variable would be left in our model if a backwards selection process were performed. (Our significance level is 0.05 for all testing purposes.) True False
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 5PPS
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Suppose that a multiple linear regression model was fit to data and that the following output resulted:
Coefficients: | ||||
(Intercept) stop distance mpg weight |
Estimate 8.63315 -0.06078 -0.03793 0.17295 |
Std. Error 5.91641 0.07368 0.08661 0.08165 |
t value 1.459 -0.825 -0.438 2.118 |
Pr(>|t|) 0.1482 0.4117 0.6626 0.0371 |
True or False? It is likely that at least one explanatory variable would be left in our model if a backwards selection process were performed. (Our significance level is 0.05 for all testing purposes.)
True
False
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