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Publication date: 11/10/2021

Example of Mean Score with Comparison Letters

This example uses the Consumer Preferences.jmp sample data table to explore the relationship between employee tenure and having school age children. The Employee Tenure column is a numeric column with values 1, 2, 3, and 4. These values have been assigned Value Labels using the Value Labels column property. To evaluate an average employee tenure using the Mean Score option in the categorical platform, assign Value Scores to the column values. For more information about column properties, see Set JMP Column Properties in Using JMP.

1. Select Help > Sample Data Library and open Consumer Preferences.jmp.

2. In the data table, right-click the Employee Tenure column heading and select Column Properties > Value Scores.

3. Enter 1 for Value and 3 for Score and click Add.

4. Enter 2 for Value and 7.5 for Score and click Add.

5. Enter 3 for Value and 15 for Score and click Add.

6. Enter 4 for Value and 25 for Score and click Add.

7. Click OK.

8. Select Analyze > Consumer Research > Categorical.

9. Select Employee Tenure and click Responses on the Simple tab.

10. Select School Age Children and click X, Grouping Category.

11. Click OK.

12. Click the Categorical red triangle and select Mean Score.

13. Click the Categorical red triangle and select Mean Score Comparisons.

Figure 3.41 Categorical Report with Mean ScoresĀ 

Categorical Report with Mean Scores

The mean employee tenure for those with school age children is 10.17 and 9.53 for those without school age children. Because the means are not statistically different, the Compare Means column in the Crosstab table is empty. If there were a difference, a letter would indicate the difference. If you had not used value scores, then the mean for those with school age children would be 2.20 and 2.057 for those without school age children.

Tip: Be aware of how your data are recorded when using the mean score option. If your data are recorded as coded numeric data with value labels, the mean value calculations are based on the numeric data. If the numeric values do not have meaning, use the Value Score column property to assign meaningful values to the response levels.

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