Overview for Overlaid Contour Plot

Use Overlaid Contour Plot to visually identify an area where the predicted means of one or more response variables are in an acceptable range. Applications that involve multiple responses present a different challenge than single response studies. Optimal variable values for one response may be far from optimal for another response. Overlaid contour plots allow you to visually identify an area of compromise among the various responses.

For more information, go to What is an overlaid contour plot?.

For example, analysts at a solar energy company want to optimize two responses: Heat flux and Insolation. Increasing the solar radiation that the focal points receive (Insolation) also tends to increase the heat flux. The analysts previously fit models that describe the relationship between the focal points and the two responses. The analysts use the overlaid contour plot to identify settings where the focal points receive a sufficient amount of solar radiation but do not generate excessive heat.

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

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 overlaid contour plot
Regression	Stat > Regression > Regression > Overlaid Contour Plot
Binary logistic regression	Stat > Regression > Binary Logistic Regression > Overlaid Contour Plot
Poisson regression	Stat > Regression > Poisson Regression > Overlaid Contour Plot
General linear model	Stat > ANOVA > General Linear Model > Overlaid Contour Plot
Screening design	Stat > DOE > Screening > Overlaid Contour Plot
Factorial design	Stat > DOE > Factorial > Overlaid Contour Plot
Response surface design	Stat > DOE > Response Surface > Overlaid Contour Plot
Mixture design	Stat > DOE > Mixture > Overlaid Contour 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 find values that optimize one or more responses, use Response Optimizer.