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Researchers at a large nutrition and weight management company are trying to build a model to predict a person’s body fat percentage from an array of variables. A variables selection method is used to build a regression model. SAS output for the final model is given in photo.  Question: What percentage of the variation in percent body fat remains unexplained, even after introducing weight and abdomen circumference into the model, and then also determine the interpretation of the slope for weight?

Researchers at a large nutrition and weight management company are trying to build a model to predict a person’s body fat percentage from an array of variables. A variables selection method is used to build a regression model. SAS output for the final model is given in photo.  Question: What percentage of the variation in percent body fat remains unexplained, even after introducing weight and abdomen circumference into the model, and then also determine the interpretation of the slope for weight?

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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Researchers at a large nutrition and weight management company are trying to build a model to predict a person’s body fat percentage from an array of variables. A variables selection method is used to build a regression model. SAS output for the final model is given in photo. 

Question: What percentage of the variation in percent body fat remains unexplained, even after introducing weight and abdomen circumference into the model, and then also determine the interpretation of the slope for weight?

Source Model Error 46 Corrected Total 48 DF Sum of Squares Mean Square F Value Pr>F 2 3053.290 1526.645 129.239 0.0000 543.379 11.813 22617.90000 Parameter R-Square Root MSE 0.8499 3.4369 Estimate Standard t Value Pr>t Error 4.742 -11.379 0.0000 0.038 4.230 0.0000 0.101 10.912 0.0000 Intercept -53.954 Weight -0.162 Abdomen circumference 1.105
Transcribed Image Text:Source Model Error 46 Corrected Total 48 DF Sum of Squares Mean Square F Value Pr>F 2 3053.290 1526.645 129.239 0.0000 543.379 11.813 22617.90000 Parameter R-Square Root MSE 0.8499 3.4369 Estimate Standard t Value Pr>t Error 4.742 -11.379 0.0000 0.038 4.230 0.0000 0.101 10.912 0.0000 Intercept -53.954 Weight -0.162 Abdomen circumference 1.105
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