Regular readers are very familiar with my refrain that many science deniers use the same tactics: bad arguments, quote-mining, appeals to authority, castigation of originators of respective theories, etc. etc. Another common thread is the complete bastardization of statistical analysis. Mark Chu-Carroll elaborates on Peter Duesberg’s misuse of statistics here, while mathematician John Allen Paulos destroys creationist/ID analysis here. I’ll highlight some of the best parts below:

For those of you who are familiar with creationist/ID arguments, you know that they take an event (say, the evolution of the human eye), and extrapolate backwards, ending with the assertion that such a structure is “too complex” for it to have evolved; it’s “statistically impossible.”

…the standard argument goes roughly as follows. A very long sequence of individually improbable mutations must occur in order for a species or a biological process to evolve.

If we assume these are independent events, then the probability of all of them occurring and occurring in the right order is the product of their respective probabilities, which is always an extremely tiny number.

Thus, for example, the probability of getting a 3, 2, 6, 2, and 5 when rolling a single die five times is 1/6 x 1/6 x 1/6 x 1/6 x 1/6 or 1/7,776 — one chance in 7,776.

The much longer sequences of fortuitous events necessary for a new species or a new process to evolve leads to the minuscule numbers that creationists argue prove that evolution is so wildly improbable as to be essentially impossible.

Of course, this is illogical for a number of reasons; most notably because, while that particular outcome may have been unlikely, *some* outcome had a high probablility of occurring. Paulos gives the example of dealing a particular hand from a deck of cards. The odds of getting a particular sequence of cards defined *a priori* are incredibly small, but the odds of being dealt *some* hand, obviously, is high.

Similarly, Mark Chu-Carroll takes apart Peter Duesberg’s use in a 1992 paper (still making the rounds) of the gambler’s fallacy in HIV transmission. Duesberg claims (emphasis mine):

Most, if not all, of these adolescents must have acquired HIV from perinatal infection for the following reasons: sexual transmission of HIV depends on an average of 1000 sexual contacts, and only 1in 250 Americans carries HIV (Table 1).

Thus, all positive teenagers would have had to achieve an absurd 1000 contacts with a positive partner, or an even more absurd 250,000 sexual contacts with random Americans to acquire HIV by sexual transmission.It follows that probably all of the healthy adolescent HIV carriers were perinatally infected, as for example the 22-year-old Kimberly Bergalis (Section 3.5.16).

Of course, as many of you can already see, just because HIV transmission may result from, on average, 1000 contacts, it doesn’t follow that one would need 250,000 random sexual contacts to contract the virus. Mark explains:

If the odds of, say, winning the lottery are 1 in 1 million, that does not mean that if I won the lottery, that means I must have played it one million times. Nor does it mean that the average lottery winner played the lottery one million times. It means that out of every one million times anyone plays the lottery, one person will be expected to win.

To jump that back to Duesberg, what he’s saying is: if the transmission rate of HIV/AIDS is 1 in 1000, then the average infected person would need to have had sex with an infected partner 1000 times.

Nope, that’s not how math works. Not even close.

Suppose we have 1000 people who are infected with HIV, and who are having unprotected sex. If we follow Duesberg’s lead, and assume that the transmission rate is a constant 0.1%, then what we would expect is that if each of those 1000 people had sex with one partner one time, we would see one new infected individual – and that individual would have had unprotected sex with the infected partner only one time.

This isn’t rocket science folks. This is damned simple, high-school level statistics.

Mark picks apart some of the other people defending Duesberg, so it’s definitely worth the read to look at the rest of the post. Meanwhile, back here at Aetiology, Chris Noble asks:

Why doesn’t Rebecca Culshaw comment? Why can’t she admit that Duesberg makes serious mathematical error?

None of the “rethinkers” have really admitted to the mathematical mistake inherent in the Duesberg Fallacy. Most of them still insist that in some way Duesberg is still correct. The few that have sufficient mathematical training choose not to comment on this issue. They neither admit to the error nor attempt to refute anything that I stated.

The likely outcome is that in a few months or a few years a new batch of “rethinkers” will read Duesberg’s articles and be convinced by the Duesberg Fallacy.

Likewise with creationists; the arguments keep popping back up like a bad game of whack-a-mole.