Basic Analysis and Graphing - SAS

294 Interactive Data Visualization Chapter 10
Additional Examples Using Graph Builder
You can clearly see the countries that consume the most oil at the top of the graph. You can also see each
country’s oil production.
Analyze Popcorn Yield
You have data about popcorn. The data includes popcorn type (plain or gourmet), how much oil was used,
the batch size (small or large), the yield, and the trial number. You want to determine how these factors
affect the popcorn yield: popcorn type, oil, and batch size.
Note: These data are artificial, but inspired from an experiment reported in Box, Hunter, and Hunter
(1978).
1. Open the Popcorn.jmp sample data table.
2. Run the attached Fit Model script attached to the data table by clicking on the red triangle next to Fit
Model and select Run Script.
A three-way ANOVA model is fit to the data.
3. Click on the disclosure icon next to Effect Tests to open the report.
The popcorn*batch interaction has a small p-value (0.0026). From this, you conclude that there is a
significant interaction between popcorn and batch.
Figure 10.32 Example of Effect Tests Output
4. Save the model predictions to the data table. From the red triangle menu next to Response yield, select
Save Columns > Prediction Formula. See Figure 10.33.
Notice that a new column is added to the data table, Pred Formula yield.
5. Save the prediction intervals to the data table. From the red triangle menu next to Response yield, select
Save Columns > Mean Confidence Interval. See Figure 10.33.
Notice that two new columns are added to the data table: Lower 95% Mean yield and Upper 95%
Mean yield.