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Sample Size and Power Analysis

November 5, 2010

Each of these four components of your study (sample size, statistical power, effect size, and significance level) are a function of the other three, meaning that altering one causes changes in the others.

Sample size is critical to ensuring the validity of your study and should be determined in the very early stages of study design The effect size of your study is critical; this unique measurement will tell you the strength or importance of a particular relationship.

Power is the measurement of the probability of committing a Type II error, which is the probability of not finding a relationship that exists in your analysis. The a priori power is unique to every study.

The alpha or significance level of your study is the probability of committing a Type I error. More simply, it is the probability of finding a relationship that does not exist. Generally, committing a Type I error is considered more severe than committing a Type II error.

The significance level measurement is unique to your study. The significance level for a study involving airbag deployment failures would not be the same as the significance level for a study involving the satisfaction of five-year-old children with a particular brand of red crayon.

via Sample Size and Power Analysis | Statistics Solutions.

Getting the Sample Size Right: A Brief Introduction to Power Analysis Link

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