Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight=-2/4+0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R² instead of simply using values of R²? Choose the correct answer below. C O A. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for regression equations with any manner of P-value. OB. The unadjusted R² increases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. OC. The unadjusted R² decreases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. O D. The unadjusted R² can only be calculated for regression equations with two or fewer predictor variables, while the adjusted R² can be calculated for regression equations with any number of predictor variables.
Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight=-2/4+0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R² instead of simply using values of R²? Choose the correct answer below. C O A. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for regression equations with any manner of P-value. OB. The unadjusted R² increases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. OC. The unadjusted R² decreases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size. O D. The unadjusted R² can only be calculated for regression equations with two or fewer predictor variables, while the adjusted R² can be calculated for regression equations with any number of predictor variables.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter4: Calculating The Derivative
Section4.CR: Chapter 4 Review
Problem 88CR
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Transcribed Image Text:Using the lengths (in.), chest sizes (in.), and weights (lb) of bears from a data set, the resulting regression equation is Weight= -274 +0.426 Length + 12.1 Chest Size. The P-value is 0.000 and the
adjusted R² value is 0.925. If an additional predictor variable of neck size (in.) is included, the P-value becomes 0.000 and the adjusted R² becomes 0.933. Why is it better to use values of adjusted R²
instead of simply using values of R²?
Choose the correct answer below.
C
O A. The unadjusted R² can only be calculated for regression equations with P-values greater than 0, while the adjusted R² can be calculated for regression equations with any manner of P-value.
O B. The unadjusted R² increases or remains the same as more variables included, but the adjusted R² is adjusted for the number of variables and sample size.
OC. The unadjusted R² decreases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size.
O D. The unadjusted R² can only be calculated for regression equations with two or fewer predictor variables, while the adjusted R² can be calculated for regression equations with any number of
predictor variables.
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