In interpreting regression statistics, we are interested in determining if the regression model/formula provides a benefit in estimation relative to simply estimating the value of all y's to be the mean of the data. One way to make this determination is to compare the standard error of the estimate and the standard deviation of the data. Which of the following statements is true? (Select one statement)

It is important that the standard error of the estimate is exactly equal to the standard deviation of the data in order to have good estimation from our regression formula.

It is important that the standard error of the estimate is larger than the standard deviation of the data in order to have good estimation from our regression formula, relative to simply using the mean of the data as an estimate.

It is always the case that the standard deviation of the data is smaller than the standard error of the estimate.

None of the above.