Specify how to code categorical predictors separately for Fit Regression Model and Fit General Linear Model. You can also choose whether to standardize continuous variables. The changes you make to the defaults remain until you change them again, even after you exit Minitab.
 Coding for categorical predictors in Regression

 Effects: Estimate the difference between each level mean and the overall mean.
 Binary: Estimate the difference between each level mean and the reference level's mean.
 Coding for factors in General Linear Model

 Effects: Estimate the difference between each level mean and the overall mean.
 Binary: Estimate the difference between each level mean and the reference level's mean.
 Standardize continuous predictors

 Do not standardize: Use your original data for the continuous predictors.
 Minimum coded as 1; maximum coded as 1: Use this option to transform the data linearly. The minimum value in the sample is coded as 1. The maximum value in the sample is coded as +1. The remaining data are coded to fall between 1 and +1.
 Subtract the mean, then divide by the standard deviation: Center the predictors and put them on a comparable scale.
 Subtract the mean: Center the predictors.
 Divide by the standard deviation: Use a comparable scale for all predictors.