Example of Multiple Correspondence Analysis
This example uses the Car Poll.jmp sample data table, which contains data collected from car polls. The data include aspects about the individuals polled, such as sex, marital status, and age. The data also include aspects about the car that they own, such as the country of origin, the size, and the type. You want to explore relationships between sex, marital status, country and size of car to identify consumer preferences.
1. Select Help > Sample Data Library and open Car Poll.jmp.
2. Select Analyze > Multivariate Methods > Multiple Correspondence Analysis.
3. Select sex, marital status, country, and size and click Y, Response.
In MCA, usually all factors are considered responses rather than some being responses and others explanatory.
4. Click OK.
Figure 7.2 Completed Multiple Correspondence Analysis Launch Window
The initial Multiple Correspondence Analysis report is shown in Figure 7.3. Note that some of the outlines are closed.
The Variable Summary report provides a concise view of the analysis completed.
The Correspondence Analysis report shows the cloud of categories of the four variables as projected onto the two principal axes. From this cloud, you can see that Americans have a strong association with the large car size while Japanese are highly associated with the small car size. Also, males are strongly associated with the small car type and females are associated with the medium car size. This information could be used in market research to identify target audiences for advertisements.
Figure 7.3 Multiple Correspondence Analysis Report
