The section Compare Averages for One Variable, compared averages across the levels of a categorical variable. To compare averages across the levels of two or more variables at once, use the Analysis of Variance technique (or ANOVA).
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Type (pharmaceutical or computer)
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Size (small, medium, big)
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Figure 3.98 Graph of Company Profits
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Select the outlier, then right-click and select Rows > Row Exclude. The point is removed, and the scale of the graph automatically updates.
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icon. Comparing mean profits is easier with bar charts than with points.
Figure 3.99 Graph with Outlier Removed
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Return to the Companies.jmp sample data table that has the data point excluded. See Discover the Relationship.
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From the Emphasis menu, select Effect Screening.
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Select the Keep dialog open option.
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Figure 3.100 Completed Fit Model Window
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Click Run. The report window shows the model results.
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To decide whether the differences in profits are real, or due to chance, examine the Effect Tests report.
Note: For complete details about all of the Fit Model results, see Model Specification in the Fitting Linear Models book.
The Effect Tests report (see Figure 3.101) shows the results of the statistical tests. There is a test for each of the effects included in the model on the Fit Model window: Type, Size Co, and Type*Size Co.
Figure 3.101 Effect Tests Report
First, look at the test for the interaction in the model: the Type*Size Co effect. Figure 3.99 showed that the pharmaceutical companies appeared to have different profits between company sizes. However, the effect test indicates that there is no interaction between type and size as it relates to profit. The p-value of 0.218 is large (greater than the significance level of 0.05). Therefore, remove that effect from the model, and re-run the model.
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Click Run.
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Figure 3.102 Updated Effect Tests Report
