How to lie with Statistics

In class last week, we were introduced to recent research on the effect of same-sex parenting on children’s welfare, specifically on high school graduation rates. We discussed how easy it can be to manipulate data in order to present a distorted view of reality.

I’ll use a fictitious example to make the point. Let’s assume you had two schools–Sir Charles Tupper and William Gladstone. Assume further that the graduation rates of the two schools are 98% and 94% for Tupper and Gladstone, respectively. Is one school substantially better at graduating its students than the other? Not really. In fact, the graduation rate at Tupper is about 4.3% higher than at Gladstone. So, Tupper is marginally better at graduating students than is Gladstone.

But, what if we compared non-graduation rates instead? Well, the non-graduation rate at Tupper is 2%, while the non-graduation rate at Gladstone is 6%. Thus, the following accurate statistical claim can legitimately be made: “Gladstone’s drop-out [non-graduation] rate is 300% greater than is Tupper’s.” Or, “Tupper non-graduation rate is 33% of Gladstone’s!” Would parents’ reactions be the same if the data were presented in this manner?

Another way to lie with statistics using graphs.

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