From the Onion: Modern Science Still Only Able To Predict One Upcoming Tetris Block.

Foreknowledge of those shapes, she explained, could lead to a breakthrough phenomenon she described as “a perpetual Tetris” of unlimited duration.

“While this remains entirely hypothetical at this moment, there exists a theoretical point at which the elimination of bottom rows occurs with such speed and efficiency that there is always enough room at the top of the matrix to accommodate new pieces,” Edelman said.

This is, surprisingly, a question about random number generators. It turns out that if you get 70,000 consecutive Z or S pieces, then you’re guaranteed to lose – try it out with Heidi Burgiel’s Java applet or the accompanying paper. Since that number is not zero, this will almost surely happen in an infinite “idealized” Tetris game. (But, of course, Tetris doesn’t have a perfect random number generator; as the Wikipedia article points out, the generator that is used repeats its numbers with small enough period that this almost certainly doesn’t happen.)

Are there any other examples of “real” math hiding in the Onion?

A list of famous quotes about statistics. I actually used the Fisher quote, “To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of”, in an e-mail to a colleague today; I believe I first saw this quote in John Cook’s blog.

It’s been a while. I blame the holidays and some Secret Big News.

Facebook’s data science team has an interesting post on the age difference between two people in a relationship. Fun fact: the average age difference in same-sex couples (of either sex) is much larger than that in opposite-sex couples. Why? I can think of two reasons:

(1) the size of the pool of potential mates is smaller for same-sex couples than for opposite-sex couples. Therefore individuals in same-sex couples have to compromise more on other dimensions, like age.

(2) the idea that both partners in a relationship should be of the same age is “conventional”, and people who are in same-sex relationships (an unconventional choice, if strictly for numerical reasons) are likely to make unconventional choices about other aspects of their relationships as well.

One possible way to find evidence for (1): is the difference between same-sex and opposite-sex couples larger in areas where there are less same-sex couples? If so, this is evidence for the “compromise” hypothesis – where there are less same-sex couples there ought to be more compromising along other dimensions. (Similarly, are the members of same-sex couples more different on other dimensions – such as educational status, race, religion, and so on – in areas with less same-sex couples?) It seems more difficult to find a way to test (2).