Basic concepts in hypothesis testing, including effect sizes, type I and type II errors, calculation of statistical power, non-centrality parameter, and applications of these concepts to twin studies.

and then looks for evidence of relationships via hypothesis testing. (This is sometimes refered to as “shotgun statistics.”) A consulting statistician to a national anti-nuclear-power group provided a ...

Statistical significance is used in null hypothesis testing, in which researchers attempt to support their theories by rejecting other explanations. Although the method is sometimes misunderstood ...

Statistical hypothesis testing is a formal process used to determine ... Sample Size Issues: Small sample sizes may lack the power to detect meaningful effects, while excessively large samples ...

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by researchers to test predictions, called hypotheses. The first step in ...

We will define the “power function” for a test and discuss its interpretation and how it can lead to the idea of a “uniformly most powerful” test. We will discuss and interpret “p-values” as an ...

The first thing any scientist does before performing an experiment is to form a hypothesis about the experiment's outcome. This often takes the form of a null hypothesis, which is a statistical ...