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
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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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