First, determine the predicted mean of the response. Then, examine the prediction interval to determine a range of likely values for a single future value.
The fitted response value (fit) is the point estimate for the specified variable settings.
The prediction interval (PI) is a range that is likely to contain a single future response for a specified combination of variable settings. If you collect another data point at the same variable settings, the new data point is likely to be within the prediction interval. Narrower prediction intervals indicate a more precise prediction.
The type of fitted response values that Minitab displays depends on the type of response variable in your model. Minitab displays the following types of fitted values:
Means for response variables that contain continuous measurements, such as length or weight.
Means for response variables that contain counts that follow the Poisson distribution, such as the number of defects per sample.
Probabilities for response variables that contain only two possible outcomes, such as pass/fail.
Standard deviations for models that are fit using Analyze