Standard error of regression analysis is known as

The correct answer is: B. variance of residual

The standard error of regression analysis is a measure of the variability of the residuals around the regression line. It is calculated as the square root of the variance of the residuals. The variance of the residuals is a measure of how much the residuals vary from the mean of the residuals. The mean of the residuals is the average of the residuals.

The standard error of regression analysis is used to make inferences about the population from which the sample was taken. For example, it can be used to construct confidence intervals for the mean of the dependent variable.

Here is a more detailed explanation of each option:

• A. average of coefficient: The average of the coefficients in a regression model is not a meaningful statistic. The coefficients in a regression model are not normally distributed, so the average of the coefficients does not have any useful interpretation.
• B. variance of residual: The variance of the residuals is a measure of how much the residuals vary from the mean of the residuals. The standard error of regression analysis is the square root of the variance of the residuals.
• C. mean of residual: The mean of the residuals is the average of the residuals. The standard error of regression analysis is not the mean of the residuals.
• D. average of residual: The average of the residuals is the mean of the residuals. The standard error of regression analysis is not the average of the residuals.