Match List I with List II


Choose the correct answer from the options given below:

Correct option is B

A. Total Sum of square - :The Total Sum of Squares represents the total variation in the data points from their mean value.
B. Sum of Square due to regression - The Sum of Squares due to Regression measures the variation in the data explained by the regression model. It represents how well the regression line fits the data.
C. Sum of Square due to curve - It represents the unexplained variation in the data, often used in the context of curve-fitting models.
D. Standard error of estimate - The Standard Error of Estimate measures the standard deviation of the residuals (the differences between actual and predicted values) in a regression model. It provides an estimate of the variability of data points around the regression line.