Basic statistical considerations for physiology: The journal <i>temperature</i> toolbox

The average environmental and occupational physiologist may find statistics are difficult to interpret and use since their formal training in statistics is limited. Unfortunately, poor statistical practices can generate erroneous or at least misleading results and distorts the evidence in the scientific literature. These problems are exacerbated when statistics are used as thoughtless ritual that is performed after the data are collected. The situation is worsened when statistics are then treated as strict judgements about the data (i.e., significant versus non-significant) without a thought given to how these statistics were calculated or their practical meaning. We propose that researchers should consider statistics at every step of the research process whether that be the designing of experiments, collecting data, analysing the data or disseminating the results. When statistics are considered as an integral part of the research process, from start to finish, several problematic practices can be mitigated. Further, proper practices in disseminating the results of a study can greatly improve the quality of the literature. Within this review, we have included a number of reminders and statistical questions researchers should answer throughout the scientific process. Rather than treat statistics as a strict rule following procedure we hope that readers will use this review to stimulate a discussion around their current practices and attempt to improve them. The code to reproduce all analyses and figures within the manuscript can be found at https://doi.org/10.17605/OSF.IO/BQGDH.对于一般环境与职业生理学家而言，由于其接受的正规统计学训练有限，往往难以解读和运用统计学方法。遗憾的是，不规范的统计实践会产生错误乃至误导性的研究结果，扭曲科学文献中的证据。若在数据收集完成后才不假思索地程式化套用统计方法，上述问题还会进一步加剧；而若将统计结果作为评判数据的严格标准（即显著与不显著之分），却完全未考量这些统计量的计算方式与实际意义，情况则会更加恶化。我们建议研究者应在研究全流程的各个环节纳入统计学考量，涵盖实验设计、数据采集、数据分析与研究结果发布等阶段。若能将统计学方法视作贯穿研究全周期的有机组成部分，诸多不规范的统计实践便可得到缓解与改善。此外，规范研究结果的发布流程，也能极大提升科学文献的整体质量。在本综述中，我们整理了研究者在整个科研流程中应当参考的多项提醒内容，以及需要逐一解答的统计学相关问题。我们期望读者不要将统计学方法视作刻板遵循的教条流程，而是借助本综述围绕自身当前的统计实践展开讨论，并尝试对其加以改进。本文手稿中所有分析与图表的复现代码，可通过以下网址获取：https://doi.org/10.17605/OSF.IO/BQGDH。