Statistics: Reasoning on Uncertainty, and the Insignificance of Testing Null

Abstract

The practice of statistical analysis and inference in ecology is critically reviewed. The dominant doctrine of null hypothesis significance testing (NHST) continues to be applied ritualistically and mindlessly. This dogma is based on superficial understanding of elementary notions of frequentist statistics in the 1930s, and is widely disseminated by influential textbooks targeted at biologists. It is characterized by silly null hypotheses and mechanical dichotomous division of results being "significant" (P < 0.05) or not. Simple examples are given to demonstrate how distant the prevalent NHST malpractice is from the current mainstream practice of professional statisticians. Masses of trivial and meaningless "results" are being reported, which are not providing adequate quantitative information of scientific interest. The NHST dogma also retards progress in the understanding of ecological systems and the effects of management programmes, which may at worst contribute to damaging decisions in conservation biology. In the beginning of this millennium, critical discussion and debate on the problems and shortcomings of NHST has intensified in ecological journals. Alternative approaches, like basic point and interval estimation of effect sizes, likelihood-based and information theoretic methods, and the Bayesian inferential paradigm, have started to receive attention. Much is still to be done in efforts to improve statistical thinking and reasoning of ecologists and in training them to utilize appropriately the expanded statistical toolbox. Ecologists should finally abandon the false doctrines and textbooks of their previous statistical gurus. Instead they should more carefully learn what leading statisticians write and say, collaborate with statisticians in teaching, research, and editorial work in journals.

Keywords

Affiliated Institutions

• University of Oulu FI

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