Proofiness – Charles Seife



Proofiness by Charles Seife is a tour of how numbers can mislead with sometimes disastrous results.  We are all guilty of assuming math-based arguments are correct.  By retelling certain historical accounts through the lens of mathematics, Seife casts new light on past events.  He mixes humor, passion and math to develop and support his arguments.

Immediately, you will benefit from the awareness of mathematical manipulation that seems to have an unchecked prevalence in mass media and business.  Think of vote counting issues, jobs reports and corporate failures.  One common thread of these events is the use of math to argue for or against whatever cause or effect is being highlighted.

Math is supposed to be an equalizer – a source of quantitative truth.  Instead, abusing math has become an accepted, popular way to skew an argument in favor of the presenter.

Aside from awareness, understanding how numbers can influence individuals, including yourself, will help you approach math-based arguments more cautiously.  Seife illustrates many times over that we should be cautious when presented with numbers as the primary reason why something is being called true or false.

From a personal perspective, if your job involves numbers, then use Proofiness as a warning to yourself.  It is a healthy reminder to be careful when using math to persuade people.  This is even more important when visualizations are used to represent the math for your argument.

Data visualizations combined with poor math can be dangerous.  We are wired to believe what can be seen and what can be calculated.  When you combine a sexy visual layer on top of bad data, it can act as a one-two punch for convincing humans that the information displayed is correct.

If you missed taking a class in college based on the book Historians’ Fallacies or skipped advanced statistics (which can teach you many things including how to lie with numbers), then read Proofiness.


For more on the danger of visual data/math, go here.

For more on statistical fallacies, go here.

For more on Charles Seife, go here.

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