Example of Sample Size Explorers
In this example, you use the Sample Size Explorers to help determine the number of units to test in a study of a new material. Suppose you are interested in demonstrating that the flammability of a new fabric being developed by your company has improved performance over current materials. Previous testing indicates that the standard deviation for time to burn of this fabric is 2 seconds.
Use the Power Explorer for One Sample Mean to calculate the number of fabric samples you need to test. You would like to design an experiment that has 90% power to detect a difference of 1.5 seconds from the current 2 seconds at a significance level of α = 0.05.
1. Select DOE > Sample Size Explorers > Power > Power for One Sample Mean.
2. Leave Test Type set to Two-Sided.
3. Leave Alpha set to 0.05.
4. For the population standard deviation assumption, leave it set to No. Sample size is calculated using the t-distribution.
5. In the profiler, use the slider or click on the red value for a text box to set the difference to detect to 1.5.
6. In the profiler, use the slider or click on the red value for a text box to set the Std Dev to 2.
7. Above the profiler, leave the target variable as Sample Size, enter 0.9 for Power, and click Go.
Note that a sample size of 21 is needed.
8. Click Remember Settings to save these settings with a setting name that you can specify.
9. Use the profiler to explore other sample size and power possibilities for your study.
Figure 29.2 One Sample Mean Power ExplorerÂ
At a significance level of 0.05, 21 fabric samples are needed to have a 90.4% chance of detecting a significant difference of 1.5 seconds in the burn time from the current 2 seconds.