1. Example Problem 3.24
Complete analysis

2. Check the data Look for missing values
Look for “impossible” values, usually data entry problems
Look for balance (or not) in the data

3. Make sure data imported correctly

4. Draw Layout and Model
Layout: Model:

5. Specify Model in software (JMP, SAS, etc.)

6. Plot the data

7. Get descriptive Statistics and error bars

8. Do One-way ANOVA which computes F-Statistic, predicted and residual values

9. The hypothesis test:

10. Since Brand is a significant treatment effect, do a means test (multiple range procedure) on treatment means.

11. Hypotheses tested by Tukey range procedure

12. Now output the Residual and Predicted values to do diagnostics on.

13. Plot and test of Normality

14. Check variances
Plot
Test

15. Assumptions met or not. Assumptions met, summarize results.
Assumptions not met, diagnose problem, either use Box-Cox transformation and rerun the ANOVA using the transformed response variable, or use a nonparametric procedure.