In JMP, data can be of different types. JMP refers to this as the modeling type of the data. Modeling Types describes the three modeling types in JMP.
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Click OK.

Although Age and Weight are both numeric variables, they are not treated the same. Results for weight and age compares the differences between the results for weight and age.
To treat a variable differently, change the modeling type. For example, in Distribution Results for Age and Weight, the modeling type for Age is ordinal. Remember that for an ordinal variable, JMP calculates frequency counts. Suppose that you wanted to find the average age instead of frequency counts. Change the modeling type to continuous, which shows the mean age.
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Doubleclick the Age column heading. The Column Info window appears.

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Change the Modeling Type to Continuous.

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Click OK.

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Repeat the steps in the example (see Example: Modeling Type Results) to create the distribution. Different Modeling Types for age shows the distribution results when Age is ordinal and continuous.
