What do we call an interval used to predict the mean for all units under certain criteria in regression?

A confidence interval is used to predict the mean for all units under certain criteria in regression analysis. This interval provides a range of values that likely contain the true population mean of the outcome variable given specific predictor values. By using a confidence interval, researchers can express the uncertainty around the estimate of the mean response, which is essential in understanding the precision of their predictions.

In the context of regression, a confidence interval indicates how confident we can be about the mean of the dependent variable for given levels of the independent variables. It is derived from the regression model and takes into account the variability of the estimates, thereby providing a range that is expected to encompass the population mean with a specified level of confidence, often set at 95%.

Other potential terms, like prediction intervals, serve a different purpose; they are specifically used to estimate the range within which a new single observation is expected to fall, rather than estimating the mean of the response variable. Hence, the essence of a confidence interval is to emphasize the estimation of group averages, making it the correct choice in the context of the question.