Four principles for improved statistical ecology
Gordana Popovic, Tanya J. Mason, Tiago A. Marques, Joanne Potts,, Szymon M. Drobniak, Roc\'io Joo, Res Altwegg, Carolyn C. I. Burns, Michael A., McCarthy, Alison Johnston, Shinichi Nakagawa, Louise McMillan, Kadambari, Devarajan, Patrick l. Taggart, Alison C. Wunderlich

TL;DR
This paper presents four guiding principles for improving statistical practices in ecology, emphasizing focused questions, appropriate models, effect sizes, and thorough reporting to enhance research validity and reproducibility.
Contribution
It introduces a clear framework of four principles to guide ecologists in designing, analyzing, and reporting their research more effectively and reliably.
Findings
Guidelines improve research focus and design.
Proper models lead to valid conclusions.
Enhanced reporting increases reproducibility.
Abstract
Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry-picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: 1. Define a focused research question, then plan sampling and analysis to answer it; 2. Develop a model that accounts for the distribution and dependence of your data; 3. Emphasise effect sizes to replace statistical significance with ecological relevance; 4. Report your methods and…
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Taxonomy
TopicsRangeland and Wildlife Management · Fire effects on ecosystems · Peatlands and Wetlands Ecology
