Statistical Data Analysis
University of London MSci PH4515
Time & Place: The lectures take place at UCL, Mondays 3:00 to 6:00, starting on 26 September 2016. Exceptionally for Monday 26 September, we will be in Physics A1 at UCL. The following weeks the room may change; please check back for further info.
Course structure: For 2016/17, as last year, the computing element of the course will not be assessed. Nevertheless, some of the statistical methods will be practiced using C++ programs. For those students without a background in C++, additional tuition will be provided.
The main lectures on Statistical Data Analysis will be from 3:00 to 5:00. For the first 6 weeks, the hour from 5:00 to 6:00 will be used to cover the basics of C++. There will be no assessed work on C++ per se, but it will be used in the statistics coursework later on. From week 7, the hour from 5:00 to 6:00 will be used to review the coursework problems and provide an oportunity for additional examples and discussion. As in previous years, the exam will only cover statistics (no C++).
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.
Problem sheets: The coursework will be due on the days of our lectures so you can hand it in then (on paper). Please write clearly on the top of the page your name, college, and degree programme (MSci, MSc or PhD). Late or emailed coursework submissions are only allowed in case of exceptional circumstances and if agreed by the lecturer. If an email submission is agreed, the entire assignment should be contained in a single pdf attachment with all of the relevant information (including your name!).
Last year's lecture notes:
More notes, books, etc.: The statistics lectures will mainly follow
This book has its own web site, which contains various data analysis resources. Also useful are:
Books on multivariate methods:
You can also download the sections on probability, statistics, and Monte Carlo from the Review of Particle Physics (K.A. Olive et al., Chin. Phys. C, 38, 090001, 2014) by the Particle Data Group.
Here is an introductory paper on Bayesian statistics: G. Cowan, Data analysis: Frequently Bayesian. Physics Today, Vol. 60, No. 4. (2007), pp. 82-3.
C++: For computing there are many other web based references, e.g.,
Archives: The archived course page for the 2003 lectures. Materials from the 2003 data analysis tutorial can be found here.
Information on computing setup: 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 email@example.com
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.