Journal Title：Journal Of The Royal Statistical Society Series A-statistics In Society

Series A (Statistics in Society) publishes high quality papers that demonstrate how statistical thinking, design and analyses play a vital role in all walks of life and benefit society in general. There is no restriction on subject-matter: any interesting, topical and revelatory applications of statistics are welcome. For example, important applications of statistical and related data science methodology in medicine, business and commerce, industry, economics and finance, education and teaching, physical and biomedical sciences, the environment, the law, government and politics, demography, psychology, sociology and sport all fall within the journal's remit. The journal is therefore aimed at a wide statistical audience and at professional statisticians in particular. Its emphasis is on well-written and clearly reasoned quantitative approaches to problems in the real world rather than the exposition of technical detail. Thus, although the methodological basis of papers must be sound and adequately explained, methodology per se should not be the main focus of a Series A paper. Of particular interest are papers on topical or contentious statistical issues, papers which give reviews or exposés of current statistical concerns and papers which demonstrate how appropriate statistical thinking has contributed to our understanding of important substantive questions. Historical, professional and biographical contributions are also welcome, as are discussions of methods of data collection and of ethical issues, provided that all such papers have substantial statistical relevance.

A 系列（社会统计）发表了高质量的论文，展示了统计思维、设计和分析如何在各行各业中发挥至关重要的作用，并总体上造福于社会。对主题没有限制：欢迎任何有趣的、主题性的和具有启发性的统计应用。例如，统计和相关数据科学方法在医学、商业和商业、工业、经济和金融、教育和教学、物理和生物医学科学、环境、法律、政府和政治、人口学、心理学、社会学和体育运动都属于该杂志的职权范围。因此，该杂志面向广泛的统计受众，尤其是专业统计学家。它的重点是针对现实世界中的问题编写良好且推理清晰的定量方法，而不是对技术细节的阐述。因此，尽管论文的方法论基础必须合理且充分解释，但方法论本身不应成为 A 系列论文的主要焦点。特别感兴趣的是关于热门或有争议的统计问题的论文，对当前统计问题进行评论或揭露的论文，以及展示适当的统计思维如何有助于我们理解重要的实质性问题的论文。我们也欢迎历史、专业和传记的贡献，以及对数据收集方法和伦理问题的讨论，前提是所有这些论文都具有实质性的统计相关性。