Sunday, 7 March 2004

Coin-toss bias

Robert Garcia Tagorda, Christopher Genovese, and Alex Tabarrok today take note of this article in Science News, which indicates that 3 researchers have found that coins, when tossed, land the same way up they started about 51% of the time.

Why hasn’t this been discovered in practice before? Interestingly, the article discusses a previous experiment with coin tossing that didn’t discover any bias:

During World War II, South African mathematician John Kerrich carried out 10,000 coin tosses while interned in a German prison camp. However, he didn’t record which side the coin started on, so he couldn’t have discovered the kind of bias the new analysis brings out.

Kerrich most likely didn’t discover the bias because some other part of his coin-tossing procedure ensured randomness. And, indeed, in a large number of trials, if there’s no bias in the starting condition (approximately equal numbers of coins are “heads” or “tails” when tossed), there will be no bias in the aggregate result—even given this finding.*

More to the point, the practical value of this finding seems minimal. The most obvious application—wagering—is precluded because no casino game that I’m aware of uses coin flips, though it’s possible that the ball in roulette and dice in craps may be similarly biased—again, given a known starting position, something that is rare in roulette at least (as the ball is under the control of the casino staff rather than the wagerers).

Proof: assume 2000 trials, 1000 starting heads and 1000 starting tails, and a .51 probability of getting the same side you started with. Of the “heads” trials, 510 will end up heads and 490 will end up tails. Of the “tails” trials, 490 will end up heads and 510 will end up tails. Thus, out of 2000 trials, you will have 1000 that result in heads and 1000 that result in tails.

More on NOMINATE

James Joyner isn’t quite convinced of Jeff Jenkins’ argument that John Kerry is more conservative relative to Democratic presidents (historically) than George Bush is liberal, using Keith Poole and Howard Rosenthal’s NOMINATE method. James writes:

The problem I have with Poole’s coding methodology is that it’s excessively time bound. To compare Bush 43 to Reagan or Kerry to Carter ignores massive shifts in public opinion during those time periods. The “center” is not a spot on a map; it’s a median of current attitudes.

There are actually two versions of Poole and Rosenthal’s methodology. The version Jenkins apparently used for his analysis (from the description in the article) is called W-NOMINATE, and only looks at a particular Congressional session (e.g. the 107th Congress, from 2001 to 2003). There’s a second version, called DW-NOMINATE, that allows comparisons over time between Congresses. In other words, using W-NOMINATE is inappropriate for comparisons over time.* James goes on to write:

I’d think the ACU/ADA ratings are much more useful than Poole’s, since the comparison is made against one’s contemporaries.

Actually, ACU and ADA ratings are essentially interchangeable with W-NOMINATE first dimension scores. But I think James is critiquing Jenkins for something that Jenkins actually didn’t do (even though the article might lead you to think he did).

It seems to me there are two related questions here: is Bush more extreme than Kerry? and, are Bush and Kerry more extreme relative to their partisan predecessors? The first question was pretty clearly answered by Jenkins in the article. The second can’t be answered by the W-NOMINATE method that Jenkins used—which, given his indication that he deliberately simplified the analysis (by using W-NOMINATE instead of DW-NOMINATE), makes it seem odd that he tried to make comparisons over time. The question I think Jenkins answered is “are Bush and Kerry more extreme relative to predecessor presidents vis à vis the Congresses they faced”—and, for that comparison, W-NOMINATE or ADA/ACU scores would work equally as well.

Update: Jeff Jenkins has a comment at Dan’s place that clarifies the situation; he did use DW-NOMINATE for the interyear comparisons, but that point was lost in the editing process. So ignore the above paragraph. ☺ He has some interesting points too in regard to Poole and Rosenthal’s book, Congress: A Political-Economic History of Roll Call Voting.

Also worth pointing out is the forthcoming APSR piece by Doug Rivers, Josh Clinton, and Simon Jackman, “The Statistical Analysis of Roll-Call Data”. There's also a recent issue of Political Analysis in which all of the articles were on ideal-point estimation (which is the technical term for NOMINATE and the Rivers-Clinton-Jackman approach). And, if you want to do it yourself, Andrew Martin and Kevin Quinn have included the Rivers-Clinton-Jackman procedure in their MCMCpack package for GNU R.

I previously discussed Kerry’s ideology here. Dan Drezner also discusses the article in question here.

* The zero point on the W-NOMINATE scale changes between Congresses, as does the unscaled variance, because there is no external anchor point. The W-NOMINATE procedure inherently normalizes the ideology scores on both dimensions to a normal distribution with mean zero and variance such that no score is outside (-1, 1).

No radar, for now

Today’s Clarion-Ledger has an article on the continued difficulty some large-county legislators are having getting an exception to the statewide ban on county sheriffs using radar.

The status of all the various bills is here, while the current law is here.