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Scottish Hill Climb races We want to predict the record time for men in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multiple Linear Relationship for the men: Coefficients for men: Term Coef SE Coef T-Value P-Value Constant -10.36 1.26 -8.23 0.000 Distance(km) 4.043 0.146 27.73 0.000 Climb (m) 0.03421 0.00220 15.57 0.000 Model Summary for men: R-sq R-sq(adj) R-sq(pred) 6.66081 98.01% 97.97% 97.77% We want to determine which of my x variables is the most important/most influential variable if our goal is to predict y in a multiple linear regression relationship. If the p-values are all the same, what is the next best measure to use to determine the most influential variable?

Scottish Hill Climb races We want to predict the record time for men in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multiple Linear Relationship for the men: Coefficients for men: Term Coef SE Coef T-Value P-Value Constant -10.36 1.26 -8.23 0.000 Distance(km) 4.043 0.146 27.73 0.000 Climb (m) 0.03421 0.00220 15.57 0.000 Model Summary for men: R-sq R-sq(adj) R-sq(pred) 6.66081 98.01% 97.97% 97.77% We want to determine which of my x variables is the most important/most influential variable if our goal is to predict y in a multiple linear regression relationship. If the p-values are all the same, what is the next best measure to use to determine the most influential variable?

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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Scottish Hill Climb races We want to predict the record time for men in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multiple Linear Relationship for the men: Coefficients for men: Term Coef SE Coef T-Value P-Value Constant -10.36 1.26 -8.23 0.000 Distance(km) 4.043 0.146 27.73 0.000 Climb (m) 0.03421 0.00220 15.57 0.000 Model Summary for men: R-sq R-sq(adj) R-sq(pred) 6.66081 98.01% 97.97% 97.77% We want to determine which of my x variables is the most important/most influential variable if our goal is to predict y in a multiple linear regression relationship. If the p-values are all the same, what is the next best measure to use to determine the most influential variable?
Transcribed Image Text:Scottish Hill Climb races We want to predict the record time for men in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multiple Linear Relationship for the men: Coefficients for men: Term Coef SE Coef T-Value P-Value Constant -10.36 1.26 -8.23 0.000 Distance(km) 4.043 0.146 27.73 0.000 Climb (m) 0.03421 0.00220 15.57 0.000 Model Summary for men: R-sq R-sq(adj) R-sq(pred) 6.66081 98.01% 97.97% 97.77% We want to determine which of my x variables is the most important/most influential variable if our goal is to predict y in a multiple linear regression relationship. If the p-values are all the same, what is the next best measure to use to determine the most influential variable?
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