Asked by mursal qaiser on May 02, 2024
Verified
The value of the sum of squares for regression SSR can never be larger than the value of total sum of squares SST.
Sum Of Squares
A statistical measure used to describe the dispersion or variation of a set of data points by squaring their deviations from the mean.
- Discern the relationship that exists among the coefficient of determination, the coefficient of correlation, and the standard error of the estimate in the realm of regression analysis.
Verified Answer
ES
Ethan ShapiroMay 04, 2024
Final Answer :
True
Explanation :
This is because SSR represents the amount of variance in the dependent variable that is explained by the regression model, while SST represents the total variance in the dependent variable. Therefore, SSR cannot be larger than SST.
Learning Objectives
- Discern the relationship that exists among the coefficient of determination, the coefficient of correlation, and the standard error of the estimate in the realm of regression analysis.