Statistics Done Wrong pdf epub mobi txt 电子书下载 2024

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Alex Reinhart

No Starch Press

2015-3-16

176

USD 24.95

Paperback

9781593276201

图书标签: 统计学统计数学 statistics 概率数据处理应用统计经济学

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发表于2024-11-21

Statistics Done Wrong epub 下载 mobi 下载 pdf 下载 txt 电子书下载 2024

Statistics Done Wrong pdf epub mobi txt 电子书下载 2024

图书描述

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong.

Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.

You'll find advice on:

Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan

How to think about p values, significance, insignificance, confidence intervals, and regression

Choosing the right sample size and avoiding false positives

Reporting your analysis and publishing your data and source code

Procedures to follow, precautions to take, and analytical software that can help

Scientists: Read this concise, powerful guide to help you produce statistically sound research.

Statisticians: Give this book to everyone you know.

The first step toward statistics done right is Statistics Done Wrong.

Statistics Done Wrong 下载 mobi epub pdf txt 电子书

著者简介

Alex Reinhart is a statistics instructor and PhD student at Carnegie Mellon University. He received his BS in physics at the University of Texas at Austin and does research on locating radioactive devices using statistics and physics.

图书目录

Statistics Done Wrong pdf epub mobi txt 电子书下载

想要找书就要到小哈图书下载中心

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立刻按 ctrl+D收藏本页

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用户评价

评分☆☆☆☆☆

当统计学科普来读了，关于p值和假设检验的部分其实是比较容易搞错，几乎日常听到的很多说法这么严格说来都根本是错的。

评分☆☆☆☆☆

坏了，以后谁也不敢相信了

评分☆☆☆☆☆

个人对于这本书的评价不太高。首先，其它领域我不太清楚，在心理学和神经科学中对统计方法的讨论反思一直就没停过，尤其是近几年的重复性危机，相关论文数不胜数，能够拿来完全取代此书内容的材料非常多，于是这本书的独特性不足，作者并没有什么厉害精辟的见解或建议。此外，鉴于读相关论文的人大多都像作者一样本身就是做统计方面工作的，如果作者写此书的目的就是给不会去读那些论文的人科普，那其内容质量也只能算马马虎虎，一般而言正确的套路应该是提出问题、回答问题、举例说明和细节整理，此书开始几章还算行，后面越来越忽视数学原理的细究，而且只提出问题而不深入解释如何具体探察与解决错误，这也许是因为我看的统计相关资料有点多而期许更多，觉得这书太简单，科普受众不一定这么认为。还是去读类似主题的统计专业书吧，此书完全可以忽略。

评分☆☆☆☆☆

当统计学科普来读了，关于p值和假设检验的部分其实是比较容易搞错，几乎日常听到的很多说法这么严格说来都根本是错的。

评分☆☆☆☆☆

心理学关于replication的crisis一定程度上揭露了一部分学者统计上“耍小聪明”（p-hacking），但是学界各大期刊接收的标准，又被publication bias左右，publication又被视为学术职称的评价标准，这就是个无解的局了。简而言之，单个研究的结果，基本上都是要打折的，要能survive replication以及meta-analysis才能算结论比较可信。对我而言这书的观点不算新了，之前的naked statistics，7 pillars of statistics，how to lie 系列都有一样的观点。