Explorations in statistics: Hypothesis tests and P values

38Citations
Citations of this article
259Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This second installment of Explorations in Statistics delves into test statistics and P values, two concepts fundamental to the test of a scientific null hypothesis. The essence of a test statistic is that it compares what we observe in the experiment to what we expect to see if the null hypothesis is true. The P value associated with the magnitude of that test statistic answers this question: if the null hypothesis is true, what proportion of possible values of the test statistic are at least as extreme as the one I got? Although statisticians continue to stress the limitations of hypothesis tests, there are two realities we must acknowledge: hypothesis tests are ingrained within science, and the simple test of a null hypothesis can be useful. As a result, it behooves us to explore the notions of hypothesis tests, test statistics, and P values. © 2009 The American Physiological Society.

Cite

CITATION STYLE

APA

Curran-Everett, D. (2009). Explorations in statistics: Hypothesis tests and P values. American Journal of Physiology - Advances in Physiology Education, 33(2), 81–86. https://doi.org/10.1152/advan.90218.2008

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free