You can choose to standardize the continuous predictors in your model. The standardized predictors are only used to fit the model and are not stored in the worksheet.
Standardizing the continuous predictors can improve the interpretation of the model for specific conditions.
- Center the continuous predictors by subtracting the mean: This method helps reduce multicollinearity, which improves the precision of the coefficient estimates. This method is helpful when your model contains highly correlated predictors, higher-order terms, and interaction terms. Each coefficient represents the expected change in the response given a one unit change in the predictor, using the original measurement scale.
- Standardize the scale of the continuous predictors by dividing by the standard deviation: This method makes the ranges of the predictors more homogenous so that you can compare the size of the coefficients. This approach is helpful when you want to know which predictors have a larger effect, while controlling for differences in scale. However, each coefficient represents the expected change in the response given a change of one standard deviation in the predictor.
Use one of the following methods to standardize your continuous predictors:
- Do not standardize: Use your original data for the continuous predictors.
- Specify low and high levels to code as -1 and +1: Use to both center the predictors and to place them on a comparable scale. Minitab uses this method in design of experiments (DOE). All data values that fall between the low and high values that you specify are transformed to fall between −1 and +1. In the table, enter low and high values or use the default minimum and maximum values in the sample.
- Continuous predictor
- Shows the names of all the continuous predictors in your model. This column does not take any input.
- Low
- Enter a value to code as −1. The default is the minimum value in the sample.
- High
- Enter a value to code as +1. The default is the maximum value in the sample.
- Subtract the mean, then divide by the standard deviation: Use to both center the predictors and to place them on a comparable scale.
- Subtract the mean: Use to center the predictors.
- Divide by the standard deviation: Use a comparable scale for all predictors.
- Subtract a specified value, then divide by another: Specify other values rather than using the mean and standard deviation estimates from the sample.
- Continuous predictor
- Shows the names of all the continuous predictors in your model. This column does not take any input.
- Subtract
- Enter the value to subtract from each continuous predictor.
- Divide By
- Enter the value that Minitab uses to divide the result of the subtraction.