Bayesian inference in non-replicated ecological studies

Published

Journal Article

Classical hypothesis testing is founded on a long-run frequency perspective that is the basis for error rates and P values used in classical statistical inference. Thus in ecological studies involving formal hypothesis testing, it is common practice to report the P value as the summary result from the test of a point null hypothesis, but many important ecological studies concern single, non-replicated events in which the P value has no clear interpretation. For the non-replicated study, Bayesian statistical inference provides an attractive alternative to classical statistical inference, as the results from a Bayesian analysis either may assume a long run frequency interpretation or may be expressed as a probability of a unique event. An example concerning trends in lake acidification is used to show that the Bayesian approach is more compatible with scientific needs and scientific judgement than is classical hypothesis testing. -Author

Full Text

Duke Authors

Cited Authors

  • Reckhow, KH

Published Date

  • January 1, 1990

Published In

Volume / Issue

  • 71 / 6

Start / End Page

  • 2053 - 2059

International Standard Serial Number (ISSN)

  • 0012-9658

Digital Object Identifier (DOI)

  • 10.2307/1938619

Citation Source

  • Scopus