Enter your data for Overlaid Contour Plot

Complete the following steps to specify the variables that you want to graph.

This dialog box varies by the type of model that you used to fit the data.

All model types except mixture designs

To perform this analysis in Minitab, go to the menu that you used to fit the model, then choose Overlaid Contour Plot. For example, if you fit a Poisson model, choose Stat > Regression > Poisson Regression > Overlaid Contour Plot.
Under Responses, move the variables that you want to include in the plot from the Available list to the Selected list. You can include up to 25 response variables.
Note
Only response variables with up-to-date models from the same analysis are in the Available list. If you do not see a response that you want, re-fit the model. For more information, go to Stored model overview.
Under Variables, from X Axis, select a variable to display on the x-axis (horizontal axis).
Under Variables, from Y Axis, select a variable to display on the y-axis (vertical axis).
Note
If your model is based on a screening design or response surface design, you can choose to display your plot using coded or uncoded units. Usually, you should use uncoded units because they allow you to view the plot in the natural units of the data.

To display an overlaid contour plot for a mixture design, choose Stat > DOE > Mixture > Overlaid Contour Plot.
Under Responses, move the variables that you want to include in the plot from the Available list to the Selected list.
Under Select components or process variables as axes, choose one of the following:

3 Components

Select to display three components on the plot. You must specify one component to display on the X Axis, the Y Axis, and the Z Axis.

2 process variables

Select to display two process variables on the plot. You must specify one process variable to display on the X Axis and the Y Axis.
Under Model Fitted in, choose whether you want to refit the model in Proportions or Pseudocomponents.
Under Component Unit in Plot(s), choose whether you want to display the components in amounts, proportions, or pseudocomponents. For more information, go to Amounts, proportions, and pseudo-components scales for representing the data in a mixtures design and What is a pseudo-component?.