When designing a study for which a statistical test will be carried out, the goal is usually to find evidence against the assumption about the theoretical world, as characterized by the null hypothesis. And if the study is well designed, there will be a high probability of rejecting the null hypothesis; this is the power of the test. This video considers the factors that affect the power, and the ways in which statistical tests can lead to incorrect conclusions.
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Notes on the video: Power and Type I and Type II Errors
A point to consider for this video:
This video demonstrates how various values affect power for means using an applet to demonstrate statistical power (external link, opens in new window). (This link points to the latest version.)The applet was developed by the Web Interface for Statistics Education (WISE) project (external link, opens in new window). We are grateful to the WISE project for permission to use their applet.