Academic Training: Practical Statistics for Particle Physicists

9, 10, 11, 12, 13 October
from 11:00 to 12:00 - Main Auditorium, bldg. 500, TH Auditorium, bldg 4, 3rd floor, on 13 October

Practical Statistics for Particle Physicists
L. LYONS, University of Oxford, GB

Lecture 1: Learning to love the errror matrix Introductory remarks. Conditional probability. Statistical and systematic errors. Combining results Binomial, Poisson and 1-D Gaussian 2-D Gaussian and the error matrix. Understanding the covariance. Using the error matrix. Estimating the error matrix. Combining correlated measurements

Lecture 2: Parameter determination by likelihood: Do's and don'ts Introduction to likelihood. Error estimate. Simple examples: (1) Breit Wigner (2) Lifetime binned and unbinned likelihood several parameters extended maximum likelihood.
Common misapprehensions:
delta(lnL) = 1/2 rule and coverage
Integrating the likelihood
Unbinned L_max as goodness of fit
Punzi effect

Lecture 3: Chi-squared and hypothesis testing Basic idea. Error estimates. Several parameters correlated errors on y. Errors on x and y. Goodness of fit. Degrees of freedom. Why assymptotic? Errors of first kind and second kind.THE paradox Kinematic fits. Toy example.

Lecture 4: Bayes, Frequentism and limits Bayes and frequentist probability. Everyday examples. Prob(data;theory) is not equal to Prob(theory;data) Bayes theorem. Bayesian prior. When priors are and are not important. Frequentist confidence intervals, and their properties. Limits calculations by Bayes, Neyman construction and Feldman-Cousins Summary of Bayes and Frequentist approaches

Lecture 5: Discovery and p-values. Distinguishing a peak, a goof, and a statistical fluctuation Why 5 sigma for discovery? Blind analyses. What p-values are and what they are not. Combining p-values. Simultaneous optimisation for discovery and exclusion Incorporating systematic effects.

Françoise Benz 73127

If you wish to participate in one of the following courses, please tell to your supervisor and apply electronically from the course description pages that can be found on the Web at: or fill in an 'application for training'form available from your Departmental Secretariat or from your DTO (Departmental Training Officer). Applications will be accepted in the order in which they are received.