Hypothesis Testing and Statistical Confidence: An Overdue Observation on the Efficacy of a Hypothesis Test
David D. Marshall, Brandi N. Falley, Mark S. Hamner

We introduce the novel argument that the general concept of statistical confidence applies both to an interval estimate of a parameter and to a hypothesis test. Measured degrees of statistical confidence are mathematical probabilities of accurate parameter identification established prior to drawing samples. Such probabilities serve as the foundation for a statistician’s expectation and conviction that a hypothesis test will correctly identify a true hypothesis, and more familiarly, that an interval estimate will properly identify a population parameter. The incidental and potentially misleading role of the P-value is discussed in the context of statistical confidence.

Full Text: PDF     DOI: 10.15640/arms.v3n1a3