Premium
Bayesian Inference in Non‐Replicated Ecological Studies
Author(s) -
Reckhow Kenneth H.
Publication year - 1990
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.2307/1938619
Subject(s) - inference , null hypothesis , statistical inference , bayesian probability , statistical hypothesis testing , bayesian inference , bayesian statistics , frequentist inference , ecology , alternative hypothesis , computer science , econometrics , frequentist probability , statistics , mathematics , artificial intelligence , biology
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 hypthesis. However, 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 judgment than is classical hypothesis testing.