Not everything that can be counted counts and not everything that counts can be counted —  Albert Einstein.

Frequentists and prior information

October 21st, 2009 Chris Lloyd Posted in Bayesian, Foundations 3 Comments »

Here is another post about wrong headed justification of Bayesian over frequentist statistics. As suggested by David Dowe in his comment on my previous post, it is worth pointing out at the beginning rather than the end that nowhere below will you find an argument against Bayesian statistics per se (though I think there are some).

In the previous post I mentioned that there are two claims that (some) Bayesians make about their approach that get me annoyed. The first is that Bayesian thinking is natural and people will naturally apply probability to unknowns if not brain-washed by a frequentist education. The second is that only Bayesians, and not frequentists, can make use of prior information. Wrong.

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Bayesian trickery

September 9th, 2009 Chris Lloyd Posted in Bayesian, Foundations 5 Comments »

It is often claimed that regular, normal people naturally think like Bayesians. Leaving aside whether we should leave the foundations of our subject to the average punter, I suspect that this might be true. But it really depends on how you frame the question. Below is a description of a class discussion exercise used by Bill Jefferys, who is a Professor of Astronomy but also an adjunct professor of statistics, teaching a course in Bayesian statistics at the University of Texas.

See if you can spot the flaws.

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ESP and Skepticism

July 29th, 2008 Chris Lloyd Posted in Bayesian, Foundations, Probability 11 Comments »

I often use ESP experiments as a vehicle to introduce hypothesis testing to students. One of the learning outcomes is that statisticians are actually easier to convince of claims of paranormal ability than lay persons . On the basis of a binomial calculation, I tell them that

I would be convinced of ESP if they could correctly select which of 5 cards I am holding more than 75 times out of 250 trials. You get 50 by guessing, and another 25 convinces the hard hearted statistician that you can bend spoons.

But I am actually telling them fibs. I would not be convinced. Does this make me irrational?

more–>I recall many years ago hearing of the so-called Soal experiment, which was in a published in book by Soul and Bateman (1954. Modern Experiments in TelepathyLondon: Faber & Faber) demonstrating telepathy. My first reaction to such claims is always rather skeptical.

In fact, the very evidence that ESP researchers use to convince us of ESP can, under mild assumptions, leads us more strongly to the conclusion that ESP is not true. This is beautifully explained in a 2003 book Probability Theory: The Logic of Science by Edwin T. Jaynes, G. Larry Bretthorst.

The experiment in question involved a woman getting 9410 trails out of 37100 correct where the chance of success under random guessing is p=0.2. This is about 26 standard deviations above the null mean and the binomial P-value is of the order of  1 in 10 to the power 139. But I for one am not convinced that she has ESP.

Frequentist hypothesis testing allows of two hypotheses only. If we are limited to two then, in this case, the relevant ones seem to be HG:she is guessing and p=0.2, or HE: she is not guessing and p>0.2. The null (HG) is overwhelmingly rejected in favour of the conclusion (HE) that she has ESP.

Bayesians can also fall for the trap of considering two hypotheses, in which case they end up in the same place as frequentists. Let LE and LG be the likelihood of the data under the null and alternative. Then the posterior probability she has ESP

eq1

Assuming that our prior probability of ESP, πE , is small, and that the likelihood of the date under the hypothesis of ESP, LE, is not small, the posterior probability of ESP is close to 1 whenever the ratio

r=LG /LE<< πE.

So it merely requires a sufficiently unlikely experimental result to overcome our prior bias against ESP and we will be convinced. So with only two hypotheses, the Bayesians are no better off than the frequentists. If my prior probability of ESP is zero then I will never be convinced. This is still formally rational but resolving to ignore any evidence of whatever strength is not rational in the informal sense.

So am I irrational to not be convinced by the Soal experiment? Do I have a prior probability of zero for ESP? I am here to tell you that I do not.

There are more than two hypotheses in play. Because there are other possible ways the data could have been generated besides a binomial experiment with p=0.2 or p>0.2. There are all sorts of possible deceptions that may have been perpetrated by the woman or by the experimenter. Let us call these various deception mechanisms that generate the data hypotheses and label them HD1,…,H Dk and assign these priors π1,…, πk that are not all extremely small. The posterior of ESP is now 

eq2

where Li is the likelihood of the data under deception hypothesis i. The various deception hypotheses make the observed data reasonably likely, just as the ESP hypothesis does. If we assume that these likelihoods are similar in magnitude to the likelihood LE then the posterior becomes

eq3

where, as before, r=LG/LE measures evidence against guessing compared to ESP. The only terms in this expression that are not likely to be tiny are πG and the πi. So the conclusion is that the posterior of ESP will be close to zero rather than close to 1. Moreover, as the ratio r=LG/LE which we think of as embodying the evidence, becomes smaller, the posterior just reverts to the priors with the guessing hypothesis eliminated. So if we start off thinking that deception is more likely than ESP then we can never be convinced of ESP.

This leads to the conclusion that an honest person may tell the truth about an extremely pertinent experimental results, and not be believed, and those who disbelieve are not being irrational. This statement makes no assumptions about who is actually correct.

The obvious, in fact only, way for ESP researchers to avoid this effect is to force us to reduce our priors on the deception hypotheses. How they could do that, I have no idea.

 

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The Optimiser’s Curse

March 8th, 2007 Chris Lloyd Posted in Bayesian, Research/Theory No Comments »

I have recently come across an interesting paper in the journal Management Science which rings a few bells for me. It concerns decision analysis and how well we can estimate the added value of the optimal decision. The bottom line is that the same data is used to make the optimal decision as is used to estimate its added value. And this results in an overly optimistic assessment.

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The Courtroom Analogy

February 7th, 2007 Chris Lloyd Posted in Bayesian, Public Interest 2 Comments »

It is fairly common practice I suspect for those of us who teach to use the court room analogy to explain hypothesis testing. The alternative is always what you suspect – guilt. The null is the status quo – innocence. The data is the evidence. There are two types of errors with different costs. But it occurs to me that if we applied basic statistical principles to the criminal system then it would look very different to what it does now.

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Beautiful Numbers

October 24th, 2006 Chris Lloyd Posted in Bayesian, Fun Stuff 1 Comment »

Artists have been inspired over the centuries by the perfect form of their beloved as a reflection of the beauty of nature, by the loneliness of clouds, and by the inevitable hand of fate that hangs over us all. Very little art has been inspired by the practice and epistemology of statistical theory. Thanks goodness, I hear you cry.

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The Bayesian Salespitch

October 5th, 2006 Chris Lloyd Posted in Bayesian, Events, Foundations 17 Comments »

I attended an interesting conference in July organised by Mark Burgman for the Australian Centre of Excellence for Risk Analysis. Not all of the talks were statistical and the standard of the coffee was a great disappointment but there was plenty of interest in seeing the interaction of engineering type risk experts, environmentalists, mathematicians, statisticians and epistemologists.

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