The correct answer is A. standard error of estimated coefficient.
The standard error of an estimated coefficient is a measure of the precision of the estimate. It indicates how much the estimate is likely to vary from its true value due to random sampling error. A larger standard error indicates that the estimate is less precise and is more likely to be different from the true value.
The weighted error of estimated coefficient is not a standard statistical term. It is possible that the question is referring to the standard error of the estimate, which is a measure of the precision of the overall regression model. However, the standard error of the estimate is not a measure of the precision of any individual coefficient.
The average of estimated coefficient is not a standard statistical term. It is possible that the question is referring to the mean of the estimated coefficients, which is a measure of the central tendency of the coefficients. However, the mean of the coefficients is not a measure of the precision of any individual coefficient.
The variance of estimated coefficient is a measure of the variability of the estimated coefficients. It indicates how much the coefficients are likely to vary from their mean value. A larger variance indicates that the coefficients are more variable and are more likely to be different from their mean value.
In conclusion, the correct answer is A. standard error of estimated coefficient.