What is the interval called that is used to predict the mean for a specific unit in regression analysis?

In regression analysis, the interval used to predict the mean outcome for a specific unit is known as the prediction interval. This interval provides a range within which we expect the actual value of a new observation to fall given the model we have fitted. It takes into account both the uncertainty in estimating the regression parameters and the variability of the data around the regression line.

The prediction interval is typically wider than the confidence interval, which is used to estimate where the mean of the dependent variable would lie for a particular independent variable value. The prediction interval reflects the additional uncertainty associated with predicting individual future outcomes, rather than just the mean.

This is a crucial distinction in regression analysis, as the prediction interval conveys more information about the potential variability of individual predictions. Understanding this concept is essential for making accurate forecasts in business and other fields where regression analysis is applicable.