How Do I Know My Sample Size Is Correct in SAS Analysis?

SAS is a powerful statistical software tool that can be used for a variety of research projects. Scientists and researchers use this tool as a validation and guide to their work. However, it is critical to use an appropriate population size for an experiment; otherwise, the experiment will be invalid. The power method is a statistical calculation used by SAS to solve this problem. It provides the level of confidence that the sample size is appropriate for your hypothesis.

Instructions

    • 1

      Gather in data inputs for the power test.

    • 2

      Determine the acceptable rate of error, which is the "t" statistic or alpha. A 5 percent error rate would equal an alpha of .05.

    • 3

      Find the mean and standard deviation of your population set. The mean is simply the average whereas the standard deviation is the number of points a typical measurement is away from the mean. Assume the mean is 20 and standard deviation is 3. Count this size of your population; assume that it is 50 samples.

    • 4

      Enter the following statements into the SAS program.

      proc power;

      onesamplemeans

      mean = 20

      ntotal = 50

      stddev = 3

      power = .;

      run;

    • 5

      Run the program through SAS, which will output a power statistic. The power statistic is a percentage term that identifies the probability that your sample size is large enough. Your power statistic should be above .95 for considerable accuracy of the sample size.

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