This example uses the Cheese.jmp sample data table, which is taken from the Newell cheese tasting experiment, reported in McCullagh and Nelder (1989). The experiment records counts more than nine different response levels across four different cheese additives.
1.
Select Help > Sample Data Library and open Cheese.jmp.
2.
Select Analyze > Fit Y by X.
3.
Select Response and click Y, Response.
The Response values range from one to nine, where one is the least liked, and nine is the best liked.
4.
Select Cheese and click X, Factor.
5.
Select Count and click Freq.
6.
Figure 6.104 Mosaic Plot for the Cheese Data
From the mosaic plot in Figure 6.104, you notice that the distributions do not appear alike. However, it is challenging to make sense of the mosaic plot across nine levels. A correspondence analysis can help define relationships in this type of situation.
Figure 6.105 Example of a Correspondence Analysis Plot
Figure 6.105 shows the correspondence analysis graphically, with the plot axes labeled c1 and c2. Notice the following:
Figure 6.106 Example of a 3-D Scatterplot
From Figure 6.106, notice the following:

Help created on 7/12/2018