A 95% prediction interval in regression context is used to estimate

A 95% prediction interval in regression context is used to estimate

• A. The population mean.
• B. Where a new individual observation will fall.
• C. The regression line.
• D. The population variance.

Answer: (A)

In regression, a 95% prediction interval shows where a new, individual observation is expected to fall for a given predictor value. It incorporates both the uncertainty in estimating the regression line (the average tendency) and the random variability of actual data around that line, so it’s wider than an interval that estimates the mean alone. If you wanted to estimate the population mean at that predictor value, you’d use a confidence interval for the mean, which is narrower because it doesn’t include the extra scatter of individual observations. So the 95% prediction interval is best interpreted as the range where a new observation is expected to fall, not the average response.

In regression, a 95% prediction interval shows where a new, individual observation is expected to fall for a given predictor value. It incorporates both the uncertainty in estimating the regression line (the average tendency) and the random variability of actual data around that line, so it’s wider than an interval that estimates the mean alone. If you wanted to estimate the population mean at that predictor value, you’d use a confidence interval for the mean, which is narrower because it doesn’t include the extra scatter of individual observations. So the 95% prediction interval is best interpreted as the range where a new observation is expected to fall, not the average response.