Common Mis-Numbers

English: Pi Pie, created at Delft University o...

Image via Wikipedia

Wouldn’t it be great it you could just read and interpret a number, and then be confident about your interpretation? If that was the case, you wouldn’t be able to buy 23 different books called “How to lie with statistics.”

Here are a few common problems I see when people try to interpret numbers.

Dislike matters just as much as like. Don’t get so focused on top box scores that you forget about bottom box scores. Brands can easily have identical top box scores and ridiculously different bottom scores.

How many times have you seen huge inexplicable spikes in your charts? Spikes are a key indicator that your sample size is too small. Be extremely nervous about numbers based on only 30 people. Be cautious of numbers based on fewer than 100 people. Check first and avoid embarrassing conclusions.

Everything on the planet is governed by rules. And one of those rules is randomness. When you’ve determined that a small sample size is not the cause of the spike, and there is no discernible explanation for the spike, consider that it may in fact be a random number. Random happens. Deal with it.

Just because a test came out significant today doesn’t mean it will with new data next week. See previous point. You will know you’ve really got something when its significant when it occurs on several unique occasions.

Happy Pi Day (to the 36th digit)!
Happy Pi Day (to the 36th digit)!‘ by Mykl Roventine via Flickr
Image is licenced under a Creative Commons Attribution licence

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