Statistical power analysis, or power analysis, is important to social science research because researchers and funding agencies usually wish to know whether a planned study has an adequate chance of detecting an effect in hypothesis testing. In other words, statistical power shows how likely it is that a scientific study can affirm a researcher’s theory. Modern hypothesis testing features empirical data and a test statistic in examining two opposing suppositions: the null hypothesis (H0) and the alternative hypothesis (Ha); the latter is often the research hypothesis or the researcher’s theory. Power analysis involves the test statistic, the significance level, the effect size, error variance, and sample size in hypothesis testing.
The empirical data for a research study are first collected from a representative sample and ...
Looks like you do not have access to this content.