Computing and Statistical Data Analysis
Royal Holloway, University of London,
phone: (01784) 44 3452, e-mail: email@example.com
Time & Place: The lectures take place at UCL, Mondays 3:00 to
6:00, starting on 30 September, UCL Physics/Union Building D103.
this is on the first floor of Union
map here, ref. D1).
Minor change to course structure: For the first four weeks, we
will use the time from 3 to 4:30 for statistics and from 4:30 to 6 for
computing. This should allow us to finish the C++ part of the course
within 4 weeks.
The computing part of the course is optional for the PhD students (check
with your supervisor) but mandatory for the MSci/MSc students.
From week five the lectures on statistical data analysis will continue
now from 3 to 5. The hour from 5 to 6 will be reserved for discussion
and if needed, overflow material from the lectures.
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.
Syllabus: A general
outline of the course topics.
The coursework will be due on the days of our lectures so you can hand
it in to me then (on paper). Please write clearly on the top of the
page your name, college, and degree programme (MSci, MSc or PhD).
Emailed coursework submissions are only allowed if for some reason you
are unable to attend the lecture, in which case the entire assignment
must be contained in a single pdf file with all of the relevant
Notes, books, etc.:
Copies of lectures are available below -- you can print them
out and bring them to the lectures. For computing there are many other web based
The statistics lectures will mainly follow
- Adrian Bevan's
computing lectures (part of the London HEP lecture programme).
- Rob Miller's
C++ Course (Imperial)
- A C++ online reference with tutorials, etc.,
- Another C++ online reference:
- G. Cowan, Statistical Data Analysis,
Clarendon Press, Oxford, 1998.
This book has its own
web site, which
contains various data analysis resources. Also useful are:
- R.J.Barlow, A Guide to the Use of Statistical Methods in the Physical
Sciences, John Wiley, 1989;
- W.T.Eadie et al., Statistical Methods in Experimental Physics,
- S.Brandt, Statistical and Computational Methods in Data
Analysis, Springer, New York, 1998;
- L.Lyons, Statistics for Nuclear and Particle Physics, CUP, 1986.
Books on multivariate methods:
- Christopher Bishop, Pattern Recognition and Machine Learning,
- T. Hastie, R. Tibshirani and J. Friedman, The Elements of
Statistical Learning, Springer, 2001.
You can also download the sections on
(pdf files) from the Review of Particle Physics by the
Particle Data Group
(K. Nakamura et al., J. Phys. G 37 (2010) 075021).
Here is an introductory paper on Bayesian statistics:
G. Cowan, Data analysis: Frequently Bayesian. Physics Today,
Vol. 60, No. 4. (2007), pp. 82-3.
Archives: The archived course page for the
2003 lectures. Materials from the
2003 data analysis tutorial can be found
Lecture Notes (2012):
Computing: Some info on how to log into the RHUL particle
physics linux machine linappserv0 from the teaching lab or your
own computer is available here.
To set up a unix environment on a windows computer you can download
and install cygwin from here. To make sure you
select the required packages and install everything correctly
please look at the information here, which is based
on the recent email that updates the
info that was here.
Once you have your account on linappserv0 you connect from any other
networked linux machine with
ssh -X firstname.lastname@example.org
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.
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.
Using ROOT: A simple standalone C++ program
for creating histograms with ROOT classes can be found
installation of ROOT libraries, set-up, etc. see your local particle
physics & computing guru.) More information on root, especially on
the interactive program, can be found on the
root home page; also the
ROOT class index is very useful. Some material from a tutorial given by
Tania McMahon can be found
And here are the slides from
Adrian Bevan's lectures on Unix and ROOT.
And here are some more resources I've found useful:
- The 2008 French
Statistics including lectures by Wouter Vekerke on
RooFit and by Andreas Hoecker on
Lectures on C++ and Root from
the DESY Summer Student Lectures by Benno List.
Introduction to Unix from the University of Strathclyde.
UNIX User Guide from CERN.
BaBar Unix Guide (SLAC).
- A simple intro to ROOT
by D. Acosta, Univeristy of Florida.
- The UNIX Reference
Desk (FAQs, links, resources).
- Mainly for Royal Holloway users: a
Guide to Computer Resources in the RH Particle Physics Group.
- DELPHI's information page on
User's Guide to the e-mail program pine (University of Washington).
- A large collection of
writeups at CERN, including
- A site with documentation on the
XEmacs editor, including the XEmacs
New User's Guide.
- Courses from the University of Strathclyde on
- Information on the debugger ddd.
- A C++ course
from Imperial College.
- Information on the C++ debugger xxgdb can be found in many places,
such as here,
which is from an
OO design course by Dennis Kafura at Virginia Tech.
- TeX Resources on the
Web (including LaTeX).
- A list of sites on
text processing and LaTeX from CERN, and the
Cambridge LaTeX site.
- A course on
computational physics from Imperial College.
- Some sites with program libraries:
- Journals, etc. (some require login from CERN or RHUL computer for access)
- Some information on Java: