I hope that the judge will now throw away his computer; modern disk drive read heads are designed to take advantage of Bayes' Theorem. --- BTW, I've been meaning to ask math-fun this question for a long time. I seem to recall that someone solved the following problem, but I've been unable to locate the solution. Bayes' Theorem takes advantage of whatever a priori information you might have to refine that probability based on a new observation. Suppose that you don't have very good information about the shape of the a priori probability curve, but may know some simple facts -- e.g., the mean, standard deviation, etc. You then do an experiment & refine the shape, but still don't have a very good idea about the precise shape. I think that someone suggested a particular family of parameterized curves for a probability distributions that is particularly well suited for Bayesian analysis/computations, in that the experiments modify the parameters of the curve, but keep the subsequent curve in the same family. Does anyone know which family of curves might be useful in this regard and/or a link to some info ? At 09:26 AM 10/11/2011, Guy Haworth wrote:

Apologies if this surfaced before, but I haven't seen it go by.

A formula for justice

Bayes' theorem is a mathematical equation used in court cases to analyse statistical evidence. But a judge has ruled it can no longer be used. Will it result in more miscarriages of justice

http://www.guardian.co.uk/law/2011/oct/02/formula-justice-bayes-theorem-misc...

Guy