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

杂志介绍

Journal Of The Royal Statistical Society Series A-statistics In Society杂志介绍

《Journal Of The Royal Statistical Society Series A-statistics In Society》是一本以English为主的未开放获取国际优秀期刊，中文名称皇家统计学会杂志系列 A-社会统计学，本刊主要出版、报道数学-SOCIAL SCIENCES, MATHEMATICAL METHODS领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE、SSCI收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为1.5，最新CiteScore 指数为2.9。

本刊近期中国学者发表的论文主要有：

• A comparison of exposure uncertainty propagation models used in epidemiological studies

  Author: Huang, Guowen; Liu, Feng

英文介绍

Journal Of The Royal Statistical Society Series A-statistics In Society杂志英文介绍

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.