Use Cube Plot
when you have a two-level factorial design or a mixture design and you want to show the relationship between the factors and a response. Each cube can show three factors. If there are only two factors, Minitab displays a square plot. Minitab draws as many cubes as necessary to show up to eight factors. Center points are displayed only for designs with five or fewer factors. Cube plots can show the following:
- The combinations of factor settings and either the data mean or fitted mean for each combination.
- The combinations of factor settings without any response means.
For mixture designs, cube plots display only data means. For more information about the types of means, go to Data and fitted means.
If you want to display fitted means for a factorial design, first use Analyze Factorial Design to fit the model for your factorial design. Minitab automatically stores the model information in your worksheet that is required to display the fitted means. For more information, go to the Stored Model Overview.
For example, an engineer wants to display the fitted means for a two-level factorial design that assesses how reaction time, reaction temperature, and type of catalyst affect the yield of a chemical reaction.
Where to find this plot
Use the version of this analysis that corresponds to the type of model you fit.
|Type of model
||Version of Cube Plot|
When to use an alternate analysis
- 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 main effects and interaction effects with fitted means, use Factorial Plots.
- 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.