Show and tell: Stats communicators share their stories

Q3 Mathematics
Hayley Bennett, Tim Chivers
{"title":"Show and tell: Stats communicators share their stories","authors":"Hayley Bennett, Tim Chivers","doi":"10.1093/jrssig/qmae028","DOIUrl":null,"url":null,"abstract":"\n One of the biggest challenges facing any statistician is communicating their work to people who don’t eat, sleep and breathe data to the extent they do. Even the most thorough courses in statistics can leave students – be they undergraduates or PhD candidates – at a loss as to how to share their knowledge effectively and persuasively, be it via a work presentation or TED talk, personal blog or magazine article, newsletter, X thread, or even just a conversation with a boss or friend.\n So how do we help the non-expert get their head around complex statistics, and at the same time find our voices as messengers? In this special feature, we ask three of the best stats communicators working today to tell us what they do, and how and why they do it. Because rarely does the data speak for itself.\n What happens when you combine creativity with data nous? Daniel Parris tells Hayley Bennett about his unorthodox journey into the statistics world, and why he started his must-read newsletter for numerate culture-vultures\n Want to create more memorable data viz? Take your time, go for a walk and remember it’s OK to suck at the start, Alli Torban tells Hayley Bennett\n As a science writer for British newspapers, author of popular books on statistical matters and twice winner of the Royal Statistical Society’s award for statistical excellence in journalism, Tom Chivers is versed in demystifying complex concepts for mainstream readers. His latest book explains Bayes’ theorem to the non-statistician.","PeriodicalId":35454,"journal":{"name":"Significance","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Significance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jrssig/qmae028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

One of the biggest challenges facing any statistician is communicating their work to people who don’t eat, sleep and breathe data to the extent they do. Even the most thorough courses in statistics can leave students – be they undergraduates or PhD candidates – at a loss as to how to share their knowledge effectively and persuasively, be it via a work presentation or TED talk, personal blog or magazine article, newsletter, X thread, or even just a conversation with a boss or friend. So how do we help the non-expert get their head around complex statistics, and at the same time find our voices as messengers? In this special feature, we ask three of the best stats communicators working today to tell us what they do, and how and why they do it. Because rarely does the data speak for itself. What happens when you combine creativity with data nous? Daniel Parris tells Hayley Bennett about his unorthodox journey into the statistics world, and why he started his must-read newsletter for numerate culture-vultures Want to create more memorable data viz? Take your time, go for a walk and remember it’s OK to suck at the start, Alli Torban tells Hayley Bennett As a science writer for British newspapers, author of popular books on statistical matters and twice winner of the Royal Statistical Society’s award for statistical excellence in journalism, Tom Chivers is versed in demystifying complex concepts for mainstream readers. His latest book explains Bayes’ theorem to the non-statistician.
展示和讲述:统计传播者分享他们的故事
任何统计学家面临的最大挑战之一就是如何向那些不像他们一样吃数据、睡数据、呼吸数据的人介绍自己的工作。即使是最全面的统计学课程,也会让学生(无论是本科生还是博士生)不知如何有效、有说服力地分享他们的知识,无论是通过工作汇报或 TED 演讲、个人博客或杂志文章、时事通讯、X 线程,甚至只是与老板或朋友的谈话。那么,我们该如何帮助非专业人士理解复杂的统计数据,同时找到我们作为信息传递者的声音呢?在这篇特稿中,我们邀请了三位当今最优秀的统计传播者,让他们告诉我们他们是怎么做的、如何做以及为什么这么做。因为很少有数据能说明问题。将创造力与数据智慧相结合会发生什么?丹尼尔-帕里斯(Daniel Parris)向海利-本尼特(Hayley Bennett)讲述了他进入统计界的非正统历程,以及他为什么要为数字文化爱好者创办必读时事通讯。 想创造更多令人难忘的数据信息吗?阿利-托班(Alli Torban)告诉海莉-贝内特(Hayley Bennett):慢慢来,去散散步,记住一开始做得很烂也没关系。 汤姆-奇弗斯(Tom Chivers)是英国报纸的科学作家,也是统计方面的通俗读物的作者,曾两次获得英国皇家统计学会颁发的新闻统计卓越奖。他的最新著作向非统计学家解释了贝叶斯定理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Significance
Significance Mathematics-Statistics and Probability
CiteScore
1.40
自引率
0.00%
发文量
96
期刊介绍: Significance is a quarterly magazine for anyone interested in statistics and the analysis and interpretation of data. Its aim is to communicate and demonstrate in an entertaining, thought-provoking and non-technical way the practical use of statistics in all walks of life and to show informatively and authoritatively how statistics benefit society.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信