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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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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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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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 Effect Tests Report) 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.
First, look at the test for the interaction in the model: the Type*Size Co effect. Graph with Outlier Removed 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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