《统计做错了》封面

统计做错了

Statistics Done Wrong

Alex Reinhart · 初版 2015 年

17人推荐
19位读者提及
23次提及

为什么值得读

  • 列举学术界真实案例,指出常见统计陷阱
  • 篇幅短小精悍且通俗易懂,读来轻松有趣
  • 帮助普通决策者识别数据分析中的漏洞

科学进步依赖于扎实的研究,而扎实的研究需要严谨的统计学。但要正确运用统计分析绝非易事,即便是最顶尖聪明的学者也常在此失手。有多少科学家运用不当,结果可能会让你大吃一惊。Statistics Done Wrong 是一本精炼且必不可少的现代科学统计失误指南,它将向你展示如何使自己的研究远离错误。你将审视近期研究中令人尴尬的错误和疏漏,了解导致这些错误发生的认知误区与科研体制政治,并开启一段革新你及你的同

Hacker News 上怎么说

  • ……适用面非常广。对于任何想做统计相关事情的人来说,都是极棒的入门书。不用搞那些花哨的 deep learning 算法,单靠朴素简单的统计学就能做这么多事,真是不可思议。- Alex Reinhart 的《Statistics Done Wrong》。里面列举了大量学术界的真实反面案例(gotchas)。文笔极佳,读起来很轻松。- Dave Eggers 的《The Circle》。这本挺让人毛骨悚然的。讲的是一家虚构的公司(有点像 Facebook 的混合体……

    …is widely applicable. Brilliant introductory for everyone who wants to do something stats related. It's amazing how much can be done with no fancy deep learning algorithms, just plain simple stats. - Statistics Done Wrong by Alex Reinhart. Plenty of gotchas with real world examples from academia. Well written and easy to read. - The Circle by Dave Eggers. This one was scary. About imaginary corporation (a blend of Facebook…

  • ……发现效应相对较小,但做决策的门外汉(红灯时能右转吗,还是说那样太危险?)可能体会不到这种细微差异。Alex Reinhart 的《Statistics Done Wrong》这本书真的帮我理清了这方面的思路。编辑:删去了最后一句话里的“interpret”以避免歧义

    …find a relatively small effect, but the layperson making decisions (do I allow right turn on red or is that dangerous?) may not get that nuance. A book that really helped clarify my thinking on this is _Statistics Done Wrong_ by Alex Reinhart. Edit: remove "interpret" from last sentence to clarify

  • ……想做对很棘手,而且很多论文都存在错误和遗漏,我倒不是说这里肯定就是这种情况,但大家应该心里有数。关于这个话题的更多内容,如果有人感兴趣的话——Statistics Done Wrong [2] [1] https://www.bls.gov/ncs/ncbr0002.pdf [2] https://www.amazon.com/gp/product/1593276206

    …tricky to get right, and plenty of papers contain errors and omissions, and I'm not necessarily saying that's the case here, but one ought to be aware. More on this topic, in case anyone is interested – Statistics Done Wrong [2] [1] https://www.bls.gov/ncs/ncbr0002.pdf [2] https://www.amazon.com/gp/product/1593276206

  • 虽然算不上严格意义上的教科书,但《Statistics Done Wrong》[1] 依然很值得一读。篇幅不长,却结合具体例子,详尽列举了统计分析最常见的被滥用方式。[1] Statistics Done Wrong: The Woefully Complete Guide https://www.amazon.com/dp/1593276206/ref=cm_sw_r_cp_apa_i_u....

    Not exactly a textbook, but good to read nonetheless is, "Statistics Done Wrong"[1]. It is a short read but is filled with all the most common ways in which statistical analysis is abused with concrete examples. [1] Statistics Done Wrong: The Woefully Complete Guide https://www.amazon.com/dp/1593276206/ref=cm_sw_r_cp_apa_i_u....

  • 我真希望能经常在这种书单里看到像 Alex Reinhart 的《Statistics Done Wrong》这样的书。它倒不是专门针对 data science 的。但它短小精悍,而且说不定能让你更有准备去辨别皇帝到底有没有穿衣服,抑或是……

    I would love to see a book like Alex Reinhart's Statistics Done Wrong make these lists more often. It's not focused on data science specifically. But it's short, sweet, and just might leave you better prepared to tell whether the emperor is wearing actual clothes, or if…

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    == Vim or Emacs == Just pick one and force yourself to use it to the exclusion of other editors. Future you will thank you later, because you'll still be using it 20 years from now. "We are typists first, programmers second" comes to mind. You need to be able to move chunks of code around, substitute things with regexes, use marks, use editor macros, etc. == 6.824: Distributed Systems == htt

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