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(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? We wish to determine the percentage of variation in depression score change that can be explained by the simple linear regression model.

(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? We wish to determine the percentage of variation in depression score change that can be explained by the simple linear regression model.

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? We wish to determine the percentage of variation in depression score change that can be explained by the simple linear regression model. First, recall the given Minitab output. Fitted Line Plot Depression score change = 6.826 + 4.802 BMI change 15- : Ø 10- 5- 0- 0.0 0.5 1.0 BMI change Depression score change 20 -0.5 S 5.38140 R-sq 21.45% Coefficients Term Coef SE Coef Constant 6.826 2.32 BMI change 4.802 2.91 1.5 T-Value 2.95 1.65 S R-Sq 21.45% R-Sq (adj) 13.59% Ⓡ P-Value 0.015 0.129 5.38140 Regression Equation Depression score change = 6.826+ 4.802 BMI change VIF 1.00 Recall that the value describes the percentage of variation in y that can be explained by x in the simple linear regression model. According to the Minitab output, to two decimal places, ² = regression model, to two decimal places, is %. %, so the percentage of variation in depression score change that can be explained by the simple linear
Transcribed Image Text:(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? We wish to determine the percentage of variation in depression score change that can be explained by the simple linear regression model. First, recall the given Minitab output. Fitted Line Plot Depression score change = 6.826 + 4.802 BMI change 15- : Ø 10- 5- 0- 0.0 0.5 1.0 BMI change Depression score change 20 -0.5 S 5.38140 R-sq 21.45% Coefficients Term Coef SE Coef Constant 6.826 2.32 BMI change 4.802 2.91 1.5 T-Value 2.95 1.65 S R-Sq 21.45% R-Sq (adj) 13.59% Ⓡ P-Value 0.015 0.129 5.38140 Regression Equation Depression score change = 6.826+ 4.802 BMI change VIF 1.00 Recall that the value describes the percentage of variation in y that can be explained by x in the simple linear regression model. According to the Minitab output, to two decimal places, ² = regression model, to two decimal places, is %. %, so the percentage of variation in depression score change that can be explained by the simple linear
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