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.

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 to fit the models, then the location of the analysis depends on the number of responses to optimize.

To optimize multiple responses, select Predictive Analytics Module > Response Optimizer. Choose the responses to optimize to produce a model diagram. Then, select Response Optimizer from the results for the model diagram.
To optimize a single response, select Response Optimizer at the top of the results for the model.

Some models from the Stat menu are also eligible models for Predictive Analytics Module > Response Optimizer.

Stat > Regression > Regression > Fit Regression Model
Stat > Regression > Binary Logistic Regression > Fit Binary Logistic Model

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.