The Insignificance of Statistical Significance Testing

Abstract

Despite their wide use in scientific journals such as The Jotirnul of\Vildlfe ,\/lanagernent, statistical hypothesis tests add very little value to the products of research. Indeed, they frequently confuse the inter- pretation of data. This paper describes how statistical hypothesis tests are often viewed, and then contrasts that interpretation with the correct one. I discuss the arbitrariness of P-values, conclusions that the null hy- pothesis is true, power analysis, and distinctions between statistical and biological significance. Statistical hy- pothesis testing, in which the null hypothesis about the properties of a population is almost always known a priori to be false, is contrasted with scientific hypothesis testing, which examines a credible null hypothesis about phenomena in nature. More meaningful alternatives are briefly outlined, including estimation and con- fidence intewals for determining the importance of factors, decision theory for guiding actions in the face of uncertain$, and Bayesian approaches to hypothesis testing and other statistical practices.