Jeon Junhyun
Department of Biotechnology, College of Life and Applied Sciences, Yeungnam University, Gyeongsan 38541, Korea.
Plant Pathol J. 2022 Jun;38(3):175-181. doi: 10.5423/PPJ.RW.03.2022.0043. Epub 2022 Jun 1.
Statistical analysis of data is an integral part of research projects in all scientific disciplines including the plant pathology. Appropriate design, application and interpretation of statistical analysis are also, therefore, at the center of publishing and properly evaluating studies in plant pathology. A survey of research works published in the Plant Pathology Journal, however, cast doubt on high standard of statistical analysis required for scientific rigor and reproducibility in the journal. Here I first describe, based on the survey of published works, what mistakes are commonly made and what components are often lacking during statistical analysis and interpretation of its results. Next, I provide possible remedies and suggestions to help guide researchers in preparing manuscript and reviewers in evaluating manuscripts submitted to the Plant Pathology Journal. This is not aiming at delineating technical and practical details of particular statistical methods or approaches.
数据统计分析是包括植物病理学在内的所有科学学科研究项目不可或缺的一部分。因此,统计分析的合理设计、应用和解释也是植物病理学研究成果发表及正确评估的核心所在。然而,一项对发表在《植物病理学杂志》上的研究工作的调查,对该杂志所要求的科学严谨性和可重复性所需的高标准统计分析提出了质疑。在此,我首先基于对已发表作品的调查,描述在统计分析及其结果解释过程中常见的错误以及经常缺失的部分。接下来,我提供可能的补救措施和建议,以帮助指导研究人员撰写稿件,并帮助《植物病理学杂志》的审稿人评估所提交的稿件。这并非旨在阐述特定统计方法或途径的技术和实际细节。