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数字一点不老实
数字一点不老实
数字一点不老实
作者:汤姆·芝华士
格式:EPUB/MOBI/AZW3
时间:2024-02-13
豆瓣评分:8.1
内容简介

  作品简介

  帮你看清数字背后的真相,不被信息轰炸忽悠

  吃饭吃药看病看报都用得到的统计思维,

  提升你的“数字感”

  我们时常遇到大量统计数据,如占比、患病率、风险值等。大量或显或隐的数字,都可能因误读或误用而扭曲真相,要读懂它们进而做出合理判断,“统计意识”不可或缺。

  本书帮读者了解数字方面的22个常见错误和花招,它们出现在评价速度和重要性的大小、准确率和排名的高低等众多情境中。本书会告诉你各种数字的采集和表达过程可能出现哪些偏差进而产生“睡前看屏幕会死人”等误导性看法,负责可信的统计数据工作又该遵循怎样的指南。




  汤姆·芝华士(Tom Chivers),科学作家,曾供职于《每日电讯报》、BuzzFeed等媒体,2018年起为自由职业者。2018年获英国皇家统计学会“新闻‘统计性’优异奖”。2017年获美国心理学会(APA)媒体奖,并列入英国科学作者奖、英国科学写作新闻奖短名单。

  大卫·芝华士(David Chivers),英国杜伦大学商学院经济学副教授,曾任牛津大学讲师。在优秀学术期刊上多有发表。研究领域包括不平等、增长和发展等。

  邓妍,心理学硕士,数学、经济学与统计学综合学科硕士。曾任投资分析师。为知名媒体担任专职翻译多年。现从事笔译和心理咨询工作。


Introduction of works

Help you see the truth behind the numbers, not be bombarded with information

I use statistical thinking to eat, take medicine, see a doctor, read a newspaper,

Improve your "number Sense"

We often encounter a large number of statistics, such as proportion, prevalence, risk value, etc. A large number of numbers, explicit or implicit, can distort the truth through misreading or misuse, and "statistical awareness" is necessary to understand them and make sound judgments.

This book helps readers understand 22 common mistakes and tricks in numbers that occur in a wide range of contexts, from speed and importance to accuracy and ranking. This book will show you how the process of collecting and presenting various numbers can go wrong, leading to misleading perceptions such as "screen time before bed is dead," and what guidelines to follow in charge of credible statistics.

Tom Chivers is a science writer who has worked for The Daily Telegraph, BuzzFeed and others, and has been freelancing since 2018. In 2018, he received the Royal Statistical Society's Excellence Award for Journalism 'Statistics'. In 2017, he received the American Psychological Association (APA) Media Award and was shortlisted for the British Science Author Award and the British Science Writing Journalism Award.

David Chivers is Associate Professor of economics at Durham University Business School and a former lecturer at Oxford University. Published in many excellent academic journals. Research areas include inequality, growth and development.

Deng Yan has a master's degree in Psychology and a master's degree in mathematics, Economics and statistics. He was an investment analyst. Worked as a full-time translator for well-known media for many years. He is currently engaged in translation and psychological counseling.

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文件名称:数字一点不老实
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