Predict
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Stat > ANOVA > General Linear Model > Predict

Use a general linear model to:

·    predict the value of the response variable (fitted values) for the combinations of variable settings that you request

·    create a confidence interval for the mean response at these combinations

·    create a prediction interval for a single observation at these combinations

·    store the prediction information in the worksheet

See Stored Model Overview for a discussion about how to use stored models. Confidence intervals cannot be calculated when the model contains random variables. Predictions are not available for models that contain nested variables.

Dialog box items

Response: Choose a response variable from the drop-down list.

Include covariates in prediction: Check to include covariate values in the predictions. If your model contains covariates but you do not include them in the prediction, Minitab averages the prediction over the covariates.

In the second drop-down list, choose whether you will enter variable settings or enter worksheet columns that contain the variable settings.

Enter individual values: Choose to enter variable settings.

Enter columns of values: Choose to enter columns from the worksheet.

Note

If you choose Enter columns of values, Minitab stores the results in the worksheet columns and does not display them in the Session window. To display the results in the Session window, check the items in the Results dialog.

Variables table

This table contains a column for each fixed variable in the model. Depending on your choice in the second drop-down list, you enter either values or columns.

·    Values - Enter at least one value for each fixed variable. The table columns must be the same length. You must enter numeric or date/time values for continuous variables. For categorical variables, choose a setting from the drop-down.

·    Columns - Enter one column for each fixed variable. Each column must contain the values for one variable. All columns must be the same length. For a continuous variable, the column must contain numeric or date/time data. For a categorical variable, the column must contain values that match the values you used to fit the model.

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