The correct answer is D. All of the mentioned.
A standard error is needed to create a prediction interval. The prediction interval must incorporate the variability in the data around the line. Investors use the residual variance to measure the accuracy of their predictions on the value of an asset.
A prediction interval is a range of values that is likely to contain the true value of a future observation. It is calculated by adding and subtracting the standard error of the estimate to the point estimate. The standard error of the estimate is a measure of the variability of the data around the line of best fit.
The residual variance is a measure of the variability of the data around the line of best fit. It is calculated by taking the sum of the squared residuals and dividing by the number of degrees of freedom. The residual variance is used to calculate the standard error of the estimate.
Investors use the residual variance to measure the accuracy of their predictions on the value of an asset. The lower the residual variance, the more accurate the predictions are likely to be.