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Statistical Inference for Particle and Astro Physics

Weizmann Institute, Rehovot, Israel

 

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Glen Cowan, Physics Department, Royal Holloway, University of London, e-mail: g.cowan@rhul.ac.uk

The website of the workshop with the contributions by myself (GDC), Alan Heavens and Kyle Cranmer is here. Below I have just collected together my parts;

G. Cowan Lecture Materials (approx. by day and still evolving):

The lectures are adapted from a course for postgraduate students 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 some exercises that we will look at in the afternoon sessions:

  • Problem on parameter estimation and its solution.
  • Problem on statistical tests and its solution.
  • Problem on multivariate methods (problem 3 on the sheet). For the multivariate analysis using TMVA you need the programs here (see also the file readme.txt).
  • An estimation problem with ML and profile likelihood (see in particular part e).
  • Some compute exercises related to discovery and limits are described here. These requires the software SigCalc which you can get in a single tarball. Here are some simple programs for working with the roostats package are SimpleCount and SimpleCLs.
  • A set of exercises for optimising a Poisson counting experiment can be found here (this includes the problem sheet and related code).

    Some other lecture notes:

    G. Cowan, Topics in statistical data analysis for high energy physics, arXiv:1012.3589 (2010).
    G. Cowan, Statistics for Searches at the LHC, arXiv:1307.2487 (2013).
    G. Cowan, Bayes Factors for Discovery (draft note).

    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;
    Ilya Narsky and Frank C. Porter, Statistical Analysis Techniques in Particle Physics, Wiley, 2014;
    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