

Statistical Data Analysis for
Particle Physics



Glen Cowan, Physics Department,
Royal Holloway, University of London, email: g.cowan@rhul.ac.uk
Class photo
Dates and times: April 12 to 16, 2010; lectures 9:00 to 11:00;
computer exercises at 14:00.
Course description:
The lectures will present an introduction to statistical methods
as used in High Energy Physics. The topics will include:
 Monday: Review of probability, Monte Carlo, parameter
estimation.
 Tuesday: Multivariate methods (I). Event selection
as a statistical test, cutbased, linear and neural network classifiers.
 Wednesday: Multivariate methods (II). Probability densitiy
estimation methods, boosted decision trees, support vector machines.
 Thursday: Significance tests for discovery and limits.
Profile likelihood methods for systematic uncertainties.
 Friday: Bayesian methods. Parameter estimation,
marginalization with MCMC, Bayesian model selection.
Lecture Notes (approx. by day and still evolving):
The lectures follow on from a course
at the University of London. The complete set of lecture notes for
that course plus other resources can be found here.
Problem sheets: Here are the statistics exercises used for the
London course (problem sheets 1 to 3 were on computing).
We will select from these:
Some books:
 G. Cowan, Statistical Data Analysis, Clarendon Press, Oxford, 1998.
 R.J.Barlow, A Guide to the Use of Statistical Methods in the Physical
Sciences, John Wiley, 1989;
 Frederick James, Statistical Methods in Experimental Physics, 2nd Edition,
World Scientific, 2006;
 S.Brandt, Statistical and Computational Methods in Data
Analysis, Springer, New York, 1998;
 L.Lyons, Statistics for Nuclear and Particle Physics, CUP, 1986.
You can also download the sections on
probability,
statistics,
and
Monte
Carlo
(pdf files) from the Review of Particle Physics by the
Particle Data Group.
Glen Cowan