This example uses the Car Physical Data.jmp sample data table to show an additional example of a logistic plot. Suppose you want to use weight to predict car size (Type) for 116 cars. Car size can be one of the following, from smallest to largest: Sporty, Small, Compact, Medium, or Large.
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From the Column Properties menu, select Value Ordering.

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Click OK.

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Select Analyze > Fit Y by X.

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Click OK.

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Markers for the data are drawn at their xcoordinate, with the y position jittered randomly within the range corresponding to the response category for that row.

If the x variable has no effect on the response, then the fitted lines are horizontal and the probabilities are constant for each response across the continuous factor range. Examples of Sample Data Table and Logistic Plot Showing No y by x Relationship shows a logistic plot where Weight is not useful for predicting Type.
Note: To recreate the plots in Examples of Sample Data Table and Logistic Plot Showing No y by x Relationship and Examples of Sample Data Table and Logistic Plot Showing an Almost Perfect y by x Relationship, you must first create the data tables shown here, and then perform steps 710 at the beginning of this section.
If the response is completely predicted by the value of the factor, then the logistic curves are effectively vertical. The prediction of a response is near certain (the probability is almost 1) at each of the factor levels. Examples of Sample Data Table and Logistic Plot Showing an Almost Perfect y by x Relationship shows a logistic plot where Weight almost perfectly predicts Type.
Note: In this case, the parameter estimates become very large and are marked unstable in the regression report.