Skip to content
HomeVideosBooks
AllTopicsTrends
BlogsPodcasts
HistoryListsWatch laterLiked videosFollowing

The videos, books, blogs and podcasts Hacker News keeps recommending, all in one place.

VideosBooksBlogsPodcastsAboutPrivacySettings

Data from Hacker News, HackerTube, HackerBooks, HackerBlogs and Open Library. Credits · Not affiliated with Y Combinator.

HomeVideosBooksBlogsPodcasts
Ctrl K
    Cover of Proofiness

    Proofiness

    Charles Seife · 2010

    In the tradition of Stephen Colbert's concept of truthiness, Proofiness explores the intersection of chicanery and mathematics. The author explores regression, false correlation, Potemkin numbers, and a variety of other sketchy techniques used to make people think that the data reflect patterns that don't exist in actuality. How to Lie With Statistics would strike me as a readalike.

    MathematicsData & StatisticsPolitics & Society
    Open LibraryAmazon
    Stats for nerds
    2recommend
    6mentions
    2people
    2011–2019years
    50% recommend50% neutral

    Mentions per year

    201120122013201420152016201720182019

    What Hacker News says

    1. folbecOct 2017
      "Proofiness" : https://www.amazon.com/Proofiness-Youre-Being-Fooled-Numbers...

      It is also a common tread in books by Tufte : https://en.wikipedia.org/wiki/Edward_Tufte

      I like "Visual Explanations: Images and Quantities, Evidence and Narrative" : https://www.amazon.com/Visual-Explanations-Quantities-Eviden...

      thread
    2. ChuckMcMDec 2012
      Recommended reading "Proofiness: The Dark Arts of Mathematical Deception" by Seife. Talks about this fallacy and others in depth.

      The best approach is multi-variate analysis. Which is to say for each correlation you find, identify another correlation that would be true (and is measurable) if the cause was what you hypothesize is the cause. Its a great way to write a paper too.

      You start with "look at this correlation", we hypothesize that cause is "Q" and now we go look at the following correlations to prove or disprove our hypothesis, ... analysis and graphs ..., as you can see our hypothesis is thoroughly {proven | disproved} by these correlations.

      If the data isn't available to do additional analysis then you are stuck trying to collect that data somehow. You can end up with inconclusive results in that case.

      thread
    3. ChuckMcMJul 2011
      I found that part annoying as well, he goes on with one of his main points:

      "What I'm concerned about is that the average scientific layman reader -- the person who assumes they are just as up-to-date on scientific matters as possible -- has no freaking idea where the real science leaves off and where the bullshit begins."

      Which I completely agree with. There is the scientific method which strives to discover truth though rigor and their is the use of 'science' in rhetoric which attempts to lend truthiness to speculation or wishful thinking.

      The blog post would have benefited greatly from taking this version of it, pulling out all of the actual things the author wanted to say, and then laying those out in a more cohesive fashion.

      For those interested in the abuse of numbers in rhetoric I can reccomend the book 'Proofiness' [1] which talks about ways people abuse mathematics as a rhetorical tool. Science is one of those things that also helps lay people feel better about believing in something.

      I agree with the original author's disappointment as to how it is being abused. But I also note that the author gets confused between how journalists report science vs what the science actually said. It is always a good idea to track down the original paper or study and read it to see what the journalist left out or simply missed.

      [1] http://www.amazon.com/dp/0670022160/

      thread
    4. ChuckMcMAug 2019
      Exactly this, and then there are people who exploit this in order to skew perceptions as described in "Proofiness: How you're being fooled by the numbers."[1]

      [1] https://www.amazon.com/Proofiness-Youre-Being-Fooled-Numbers...

      thread
    5. ChuckMcMJan 2014
      Sigh what a squishy article. What is the methodology? What is the sampling error? What does "OK" mean relative to "Good" ? This reminds me of the anecdotes in "Proofiness"[1] which talk about how the news industry figured out they could manufacture news by taking a poll.

      [1] http://www.amazon.com/Proofiness-Youre-Being-Fooled-Numbers/...

      thread
    6. ChuckMcMFeb 2012
      Yes, but that risk has flavors. Funding the Moon Landing was exceptionally high risk [1] because NASA did not yet have a minimum viable product. VC's that I've met don't usually take that level risk, they wait until there is at least some expectation that the team can deliver something (hence the MVP requirement in many series A rounds).

      [1] In "Proofiness: The Dark Arts of Mathematical Deception", Charles Seife claims that NASA asked GE to calculate the chances of success in the Moon Landing and came out with 5%. http://www.amazon.com/Proofiness-Dark-Arts-Mathematical-Dece...

      thread

    Related

    Book of ProofRichard Hammack
    2012–2026

    Book of Proof

    Richard Hammack
    54 recommend · 86
    Cover of How to prove it
    2007–2026

    How to prove it

    Daniel J. Velleman
    78 recommend · 129
    Cover of Proof and the Art of Mathematics
    2022–2023

    Proof and the Art of Mathematics

    Joel David Hamkins
    3 recommend · 3
    Cover of Proofs and types
    2010–2026

    Proofs and types

    Jean-Yves Girard
    6 recommend · 14
    Cover of Proofs from the book
    2010–2026

    Proofs from the book

    Martin Aigner
    28 recommend · 60
    Cover of Mathematical proofs
    2013–2024

    Mathematical proofs

    Gary Chartrand
    17 recommend · 23
    Cover of Metamagical Themas
    2007–2026

    Metamagical Themas

    Douglas R. Hofstadter
    45 recommend · 98
    Cover of A mathematical introduction to logic
    2008–2025

    A mathematical introduction to logic

    Herbert B. Enderton
    6 recommend · 11