Here is an analogy. Imagine I am standing near a large wooden barn with an enormous machine gun. I place a blindfold over my eyes and – laughing maniacally – I fire off many thousands and thousands of bullets into the side of the barn. I then drop the gun, walk over to the wall, examine it closely for some time, all over, pacing up and down: I find one spot where there are three bullet holes close to each other, and then I draw a target around them, announcing proudly that I am an excellent marksman. You would, I think, disagree with both my methods and conclusions for that deduction. But this is exactly what has happened in Lucia’s case: the prosecutors have found 7 deaths, on one nurse’s shifts, in one hospital, in one city, in one country, in the world, and then drawn a target around them. A very similar thing happened with the
Sally Clark cot death case.
Before you go to your data, with your statistical tool, you have to have a specific hypothesis to test. If your hypothesis comes from analysing the data, then there is no sense in analysing the same data again to confirm it. This is a rather complex, philosophical, mathematical form of circularity: but there were also very concrete forms of circular reasoning in the case. To collect more data, the investigators went back to the wards to find more suspicious deaths. But all the people who have been asked to remember ‘suspicious incidents’ know that they are being asked because Lucia may be a serial killer. There is a high risk that “incident was suspicious” became synonymous with “Lucia was present”. Some sudden deaths when Lucia was not present are not listed in the calculations: because they are in no way suspicious, because Lucia was not present.