Overview for Factorial Plots

Use Factorial Plots when you want to plot the relationships between the response and the variables.

Use a main effects plot to display the relationship between the response and individual variables.
Use an interaction plot to display how the relationship between one variable and a fitted response depends on the value of a second variable.

For example, researchers at a motor vehicle bureau want to illustrate their general linear model results that find a significant interaction effect between driver experience and road type on the time spent on making steering corrections.

This analysis uses a model that you fit and that Minitab stores. For more information, go to Stored model overview.

Note

For mixture designs, factorial plots do not use a stored model and display only data means.

Where to find this plot

If you use the Predictive Analytics Module to create a Linear Regression Model or a Binary Logistic Regression model, then select the analysis from the top of the results. If you create the model from the Stat menu, then use the version of this analysis that corresponds to the type of model you fit.

Type of model	Version of Factorial Plots
Regression	Stat > Regression > Regression > Factorial Plots
Binary logistic regression	Stat > Regression > Binary Logistic Regression > Factorial Plots
Poisson regression	Stat > Regression > Poisson Regression > Factorial Plots
General linear model	Stat > ANOVA > General Linear Model > Factorial Plots
Mixed effects model	Stat > ANOVA > Mixed Effects Model > Fit Mixed Effects Model
Screening design	Stat > DOE > Screening > Factorial Plots
Factorial design	Stat > DOE > Factorial > Factorial Plots
Response surface design	Stat > DOE > Response Surface > Factorial Plots
Mixture design	Stat > DOE > Mixture > Factorial Plots

When to use an alternate analysis

If you do not have a stored model, use data means instead of fitted means in Main Effects Plot and Interaction Plot. For more information about the types of means, go to Data and fitted means.
If you have a stored model and want to predict the value of the response variable for combinations of variable settings that you specify, use Predict.
If you have a stored model and want to plot the relationship between a fitted response and two continuous variables with contour lines in a two-dimensional view, use Contour Plot.
If you have a stored model and want to plot the relationship between a fitted response and two continuous variables with a three-dimensional response surface, use Surface Plot.
If you have at least one stored model and want to identify an area where the predicted means of one or more response variables are in an acceptable range, use Overlaid Contour Plot.
If you have at least one stored model and want to find values that optimize one or more responses, use Response Optimizer.