There’s hardly anything we talk about or write about that doesn’t have at least one statistic as an integral part of it — sports, politics, economics, and so on.

Which is OK, I suppose. After all, what harm can statistics do? They’re just numbers.

Well, they can do plenty of harm, when they’re used to give an appearance of solidity to something that is nothing more than pure wind.

(By the way, that beautiful phrase about solidity and wind is George Orwell’s creation, not mine. I wish it were.)

Anyway, let me give you an example.

Following is a paragraph taken from an article that appeared in the July 31, 1995, edition of the San Francisco Chronicle.

"The typical black student with combined Scholastic Aptitude Test scores between 701 and 850 had a 56% likelihood of graduating from a college where the average student’s score was 900. But his or her likelihood of graduating fell to 39% at a more selective school, where the average student’s score was 1000."

Now just what did the paragraph say that was useful? In my opinion, nothing. And yet the writer of the article built an entire thesis supporting so-called affirmative action around it and other similar paragraphs.

The statistics themselves, assuming they were properly and honestly gathered, were objective and unbiased. The thesis based upon an interpretation of those same statistics was not.

Nor could it be, for the simple reason that while a measurement can be neutral, an opinion, inference, or judgment about the meaning of that measurement cannot.

Think about it.