Chapter 16
Prospective Sample Size and Power
Use the DOE > Sample Size and Power command to answer the question “How many runs do I need?” The important quantities are sample size, power, and the magnitude of the effect. These depend on the significance level, alpha, of the hypothesis test for the effect and the standard deviation of the noise in the response. You can supply either one or two of the three values. If you supply only one of these values, the result is a plot of the other two. If you supply two values, the third value is computed.
The Sample Size and Power platform can answer the question, “Will I detect the group differences I am looking for, given my proposed sample size, estimate of within-group variance, and alpha level?” In this type of analysis, you must approximate the group means and sample sizes in a data table as well as approximate the within-group standard deviation (σ).
The sample size and power computations determine the sample size necessary for yielding a significant result, given that the true effect size is at least a certain size. It requires that you enter two out of three possible quantities; difference to detect, sample size, and power. The third quantity is computed for the following cases:
• difference between a one sample mean and a hypothesized value
• difference between two sample means
• differences in the means among k samples
• difference between a standard deviation and a hypothesized value
• difference between a one sample proportion and a hypothesized value
• difference between two sample proportions
• difference between counts per unit in a Poisson-distributed sample and a hypothesized value.
The calculations assume that there are equal numbers of units in each group. You can apply this platform to more general experimental designs, if they are balanced and an adjustment for the number-of-parameters is specified.
You can also compute the required sample sizes needed for reliability studies and demonstrations.
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