Research and statistical analysis help us understand how the world works, how effective medications and treatments are, what influences our health, the best approach for business practices, and much ...

In applied research, an effect size is specified in advance and defines a threshold for decision-making. Power analyses of a specific desired effect size may then be carried out before an experiment ...

In the Neyman-Pearson theory of hypothesis testing it is customary to calculate significance levels and power functions on the assumption that the sample size is fixed. The main purpose of this paper ...

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 ...

If the claim is really false but the researcher decides, based on the evidence, it’s true – a false positive – they commit what’s called a Type 1 error. If the claim is really true but the researcher ...

Statistical testing provides a paradigm for deciding whether the data are or are not typical of the values expected when the hypothesis is true. Because our objective is usually to detect a departure ...

We consider estimators for the change-point in a sequence of independent observations. These are defined as the maximizing points of weighted U-statistic type processes. Our investigations focus on ...

I've recently begun to publish small excerpts and arguments from my forthcoming work, The Myth of Sex Addiction. As I've done so, I've heard from sex addiction proponents who argue that I must accept ...

The probability that the null hypothesis will be rejected when it is actually true is called the false positive rate and is determined by the significance level of the test (called alpha which is ...