While there's a whole branch of physics called statistical physics (probably a misleading title) physicists often get only a few hours of statistical training in their undergraduate degrees. This is surprising to some who think of physicists as the most mathematical of scientists. In fact you can find a diversity of statistical crimes/accidents in physics papers (and I'm sure you can find them in my own). In partial acknowledgement of this, I organised this Royal Society Discussion Meeting and edited this volume of the Philosophical Transactions of the Royal Society “Signal Processing and Inference for the Physical Sciences” with the excellent Prof Tom Maccarone (now at Texas Tech Astrophysics and Astronomy). Our goal was to expose physical scientists to some new topics in statistical inference and some data analysts to physical challenges. Lots of the volume is free and there are also talks from the authors and slides on this page. We provide an introduction "Inference for the Physical Sciences" which we hope can serve as a jumping off point for physical scientists wanting to use statistical tools. Max Little also wrote an article highlighting some challenges in signal processing in biophysics "Signal processing for molecular and cellular biological physics" putting some of our other work in context (see previous blog articles on finding steps beneath the noise and on molecular dance steps). For those with an interest in Machine Learning I think the talks by Bishop, Gharamani, Roberts and Hyvärinen are worth a look. Nick

"Probabilistic physics" would be a more accurate name for it, but of course we are stuck with "statistical".

ReplyDeleteI would argue that mathematicians are the most mathematical of scientists (subject to the argument of whether a mathematician is also a scientist, for which I am firmly on the side of 'yes').

It seems like the workshop was very successful, which is excellent to hear.