It is already known that four attributes are important for laptop design: hard-disk size, processor speed, battery life, and selling price. The data gathered for this study are used to determine which of four laptop attributes (Hard Disk, Speed, Battery Life, and Price) are most important. It also assesses whether there are Gender or Job effects associated with these attributes.
1.
Select Help > Sample Data Library and open Laptop Runs.jmp.
2.
Click the green triangle next to the Open Profile and Subject Tables script.
The script opens the Laptop Profile.jmp and Laptop Subjects.jmp data tables.
3.
Select Analyze > Consumer Research > Choice.
4.
From the Data Format list, select Multiple Tables, Cross-Referenced.
5.
Click Select Data Table under Profile Data and select Laptop Profile.jmp. Select Choice ID and click Profile ID.
6.
Select Hard Disk, Speed, Battery Life, and Price and click Add.
7.
Select Survey and Choice Set and click Grouping.
Figure 5.22 Profile Data Window for Laptop Study
8.
Open the Response Data outline.
9.
From the Select Data Table list, select Laptop Runs.jmp.
Select Response and click Profile ID Chosen.
Select Choice1 and Choice2 and click Profile ID Choices.
Select Survey and Choice Set and click Grouping
Select Person and click Subject ID. The Response Data window is shown in Figure 5.23.
Figure 5.23 Response Data Window for Laptop Study
11.
Open the Subject Data outline.
12.
From the Select Data Table list, select Laptop Subjects.jmp.
13.
Select Person and click Subject ID.
14.
Select Gender click Add.
Figure 5.24 Subject Data Window for Laptop Study
1.
Click Run Model.
Figure 5.25 Laptop Effect Summary
The Effect Summary report shows that Hard Disk is the most significant effect. You can reduce the model by removing terms with a p-value greater than 0.15. This process should be done one term at a time. Here, Gender*Speed is the least significant effect, with a p-value of 0.625.
2.
In the Effect Summary report, select Gender*Speed and click Remove.
Figure 5.26 Laptop Results
Once Gender*Speed is removed from the model, all effects have a p-value of 0.15 or less. Therefore, you use this as your final model.
Figure 5.27 Laptop Profiler Results for Females
Tip: If your utility profiler does not look like Figure 5.27, click the red triangle next to Utility Profiler and select Appearance > Adapt Y Axis.
Figure 5.28 Laptop Profiler Results for Males in Development
The interaction effect between Gender and Hard Disk is highly significant, with a p-value of 0.0033. See Figure 5.26. In the Utility Profilers, check the slope for Hard Disk for both levels of Gender. You see that the slope is steeper for females than for males.
In the Laptop Runs. jmp sample data table, click the green triangle next to the Choice Reduced Model script.
Note that the Probability Profiler is for Gender = F. You can change this later.
Figure 5.29 Probability Profiler with Text Entry Area for Price
6.
Click the $1000 label above the Price cell in the profiler, type $1,200, and click outside the text box.
Figure 5.30 Laptop Probability Profiler Results with Baseline Effects
In the Laptop Runs.jmp sample data table, click the green triangle next to the Choice Reduced Model script.
3.
4.
For Alternative 1, set Hard Disk to 40 GB, Speed to 1.5 GHz, Battery Life to 4hours, and Price to $1,000.
5.
For Alternative 2, set Hard Disk to 40 GB, Speed to 2.0 GHz, Battery Life to 6 hours, and Price to $1,200.
6.
For Alternative 3, set Hard Disk to 80 GB, Speed to 2.0 GHz, Battery Life to 4 hours, and Price to $1,500.
Figure 5.31 Multiple Choice Profiler for Females
7.
For Alternative 1, set Hard Disk to 80 GB and Price to $1,200.
Figure 5.32 Multiple Choice Profiler with Improved Laptop

Help created on 7/12/2018