{"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":"12 4","pages":""},"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.
SignificanceMathematics-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.