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 findings in sufficient detail so that your research is valid and reproducible. Listed in approximate order of importance, these principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well-defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to false positives and poor replicability. Correct and appropriate statistical models give sound conclusions, good reporting practices and a focus on ecological relevance make results impactful and replicable. Illustrated with an example from a recent study into the impact of disturbance on upland swamps, this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods.

翻译：近年来，统计方法的误用日益引起关注，尤其是不良实验设计、选择性报告和报告不充分等做法的普遍存在令人担忧。这些失误大多是无意造成的，其在生态学中的发生频率并不高于其他科学学科，只要给出正确指导，其中许多问题很容易得到纠正。源于2020年国际统计生态学会议的讨论，我们展示了生态学家如何遵循四项指导原则开展研究以实施具有影响力的统计研究实践：1. 界定明确的研究问题，然后规划采样和分析以回答该问题；2. 建立能够解释数据分布和依赖性的模型；3. 强调效应大小，用生态相关性取代统计显著性；4. 充分详细地报告方法和发现，确保研究有效且可重复。这些原则按重要性大致排序，为实验设计和报告提供了一个框架，防止不严谨的做法。从明确的研究问题入手，可使研究人员创建高效的研究来回答该问题，并防止导致假阳性和可重复性差的不良研究实践。正确且恰当的统计模型能得出可靠的结论，良好的报告实践以及对生态相关性的关注能使结果具有影响力和可重复性。本文以近期一项关于干扰对高地沼泽影响的研究为例，阐述了选择和实施有效统计实践的基本原理，并为寻求改进统计方法使用的生态学家提供了实用指导。