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Statistical Data Analysis
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Glen Cowan,
Royal Holloway, University of London,
phone: (01784) 44 3452, e-mail: g.cowan@rhul.ac.uk
Time & Place: The 2025/26 course takes place Mondays 2-5 pm starting 29 September ending 8 December
(11 weeks with no reading week).
The lectures will take place in London in Stewart House, Room 2. The entrance to Stewart House is through
Senate House, Malet Street, London WC1E 7HU -- here is a map.
Once in Senate House go up the big staircase, turn left and through the corridor past the Royal Holloway sign.
The core material is presented
in the first two hours; the third hour is used for examples and
discussion.
Moodle page: U. of London MSc and MSci students should access the
course through its RHUL
moodle page.
Aims: This series of lectures
is intended for PhD students in Particle Physics and it also forms
the University of London MSci course PH4515. The purpose of the lectures
on probability and statistics is to
present the basic mathematical tools needed for the analysis of
experimental data. The methods will be practiced by writing and
running short computer programs.
Although the examples used in the course often relate to particle
physics this is done in a relatively simple way and MSci students from
other physics areas should not find this too great a difficulty.
Computing: The statistical methods will be practiced
using computer programs in python or C++. Students
should have some familiarity with at least one of these languages
or be willing to use additional resources to acquire the needed
computing skills.
Syllabus: A general
outline of the course topics.
Slides and notes:
Problem sheets: There are 9 problem sheets due on Mondays
at 18:00 from lecture weeks 3 through 11. Scan/merge everything (including code) into a single pdf file with filename:
YourName_stat_prob_sheet_n.pdf (n=1,2,...). MSc/MSci students: submit via moodle. PhD students: email to me with the
exact subject line: statistics problem sheet n (n=1,2,...).
Books on statistical methods:
- The course mainly follows: G. Cowan, Statistical Data Analysis,
Clarendon Press, Oxford, 1998; more here.
- 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;
- Ilya Narsky and Frank Porter, Statistical Analysis
Techniques in Particle Physics, Wiley, 2013.
- L.Lyons, Statistics for Nuclear and Particle Physics, CUP, 1986.
Books on multivariate methods:
-
Christopher Bishop, Pattern Recognition and Machine Learning,
Springer, 2006.
- T. Hastie, R. Tibshirani and J. Friedman,
The Elements of
Statistical Learning, 2nd edition, Springer, 2009.
- Gareth James, Daniela
Witten, Trevor Hastie and Robert Tibshirani, An Introduction to
Statistical Learning with Applications in R:
book
and
lectures.
Some additional notes/resources:
Computing:
Some more lectures on statistics I've given:
- Errors on errors: refining analyses with the Gamma Variance Model,
Carnegie Mellon U. STAMPS seminar (12 Nov 2021), slides,
video.
- Academic training lectures
on
Statistics at the LHC, CERN, 14-17 June, 2010.
-
Lectures on
statistical methods for particle physics at Tsinghua University,
12-16 April, 2010.
- Seminar on
recent progress in multivariate methods for particle physics,
Weizmann Institute of Science, 17 Jan 2010.
- Statistical Methods in Particle Physics at SUSSP65,
St Andrews, 16-29 August 2009:
lecture 1,
lecture 2,
lecture 3
- Two lectures on Bayesian methods given at the DESY
Statistics
School (part of the Helmholtz Alliance Physics at the Terascale initiative),
29 September - 2 October 2008:
lecture 1 (ppt,pdf),
lecture 2 (ppt,pdf).
- The materials for my lectures on
advanced statistical methods for data
analysis (multivariate methods) for the University of Mainz
(Klausurtagung des GK "Eichtheorien -- experimentelle Tests...",
Bullay/Mosel, 15-17 September, 2008). These are updated versions of
my lectures on multivariate statistical
methods in particle physics (CERN Academic Training Lectures,
16-19 June, 2008).
- The CERN Summer Student Lecture statistics lectures are
here.
- Bayesian statistics
at the LHC (and elsewhere), Cavendish-DAMTP HEP phenomenology seminar,
Cambridge, 7 March 2008.
- Lectures on Statistics at the CERN-FNAL Hadron Collider Physics School:
lecture 1 and
lecture 2,
CERN, 6 and 8 June, 2007.
- Bayesian statistical methods
for parton analyses, talk at DIS2006, Tsukuba, 22 April, 2006.
Archives -- Statistical Data Analysis old lectures:
Information on computing setup: Some info on how to log into
the RHUL particle physics linux machine linappserv1 from the teaching
lab or your own computer is
available here.
Once you have your account on linappserv0 you connect from any other
networked linux machine with
ssh -X username@linappserv0.pp.rhul.ac.uk
where for "username" you substitute your login name, and then enter
your password. You will have been given information on computer
security and on how to change your password. It is your
responsibility to read and follow these rules.
The -X qualifier above should allow you to open up an "x-window". You can
check this by typing at the prompt
xclock &
which should open up a clock in a small window. If it doesn't work, try
using -Y or -XY.
Your default shell is bash. Your account should have in the
home directory a file called .bash_profile (check this with
ls -la). If it isn't there, you can copy this
.bash_profile to your
home directory. This defines certain aliases and environment
variables automatically when you log in. In particular, it
defines the environment variable ROOTSYS, which you need for
the ROOT programs we will use.
You can also copy to your home directory the file
.emacs, which will
set some defaults for the emacs editor.
Glen Cowan