Overview for Response Optimizer

Use Response Optimizer to identify the combination of input variable settings that optimize a single response or a set of responses. Minitab calculates an optimal solution and draws an optimization plot. This interactive plot allows you to change the input variable settings to perform sensitivity analyses and possibly improve upon the initial solution.

The Response Optimizer on the Stat menu includes optimization for multiple responses.
The Response Optimizer on the Predictive Analytics Module includes optimization for a single response.

For more information, go to What is response optimization?.

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

Where to find this analysis

If you use the Predictive Analytics Module, 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	Path
Regression	Stat > Regression > Regression > Response Optimizer
Binary logistic regression	Stat > Regression > Binary Logistic Regression > Response Optimizer
Poisson regression	Stat > Regression > Poisson Regression > Response Optimizer
General linear model	Stat > ANOVA > General Linear Model > Response Optimizer
Screening design	Stat > DOE > Screening > Response Optimizer
Factorial design	Stat > DOE > Factorial > Response Optimizer
Response surface design	Stat > DOE > Response Surface > Response Optimizer
Mixture design	Stat > DOE > Mixture > Response Optimizer

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.