Cherry picking

We presented a collection of fraudulent data practices in our previous post. Now, let’s consider each fraudulent technique in turn, beginning with the “Texas sharpshooter fallacy” or cherry picking: the practice of selecting results that fit your claim and excluding those that don’t. According to the good folks at Geckoboard (a London-based consulting firm), this practice is “[t]he worst and most harmful example of being dishonest with data. When making a case, …. people often only highlight data that backs their case, rather than the entire body of results. It’s prevalent in public debate and politics, where two sides can both present data that backs their position. Cherry picking can be deliberate or accidental. Commonly, when you’re receiving data second hand, there’s an opportunity for someone choosing what data to share to distort the truth to whatever opinion they’re peddling. When on the receiving end of data, it’s important to ask yourself: ‘What am I not being told?’”

About F. E. Guerra-Pujol

When I’m not blogging, I am a business law professor at the University of Central Florida.
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1 Response to Cherry picking

  1. Pingback: Publication bias | prior probability

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