Statistical Methods in Particle Physics
Introduction
"Statistics is the grammar of science."  Karl Pearson
For those of you who are keen to extend their education in the field of particle physics, it may be interesting to attend this course. The lecture and especially the handson exercises are particularly relevant for those who always wanted to know how to exactly interpret the discovery plot for the Higgs boson or the exclusion limits for New Physics at the LHC, and who are interested to learn more about data analysis techniques in general.
Supporting material
The following text books can be advised as a good starting point for graduate level students:
 Cowan: Statistical Data Analysis (Oxford Science Publications)
 Barlow: Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences (Manchester Physics Series)
 Lyons: Statistics for Nuclear and Particle Physicists (Cambridge University Press)
 P.R.Bevington and D.K.Robinson "Data reduction and error analysis for the physical sciences", WBC/McGrowHill, 1992
 Blobel, Lohrmann: Statistische Methoden der Datenanlyse (Teubner, in German) Ebook: http://www.desy.de/~blobel/eBuch.pdf
Formalia
Lectures (Link to LSF) every Monday 14:15  16:00, starting October 12th at INF 227 (KIP) / SR 3.404
Tutorials every Monday 16:00  18:00, starting October 12th at CIP Pool, KIP / 1.401
Please sign up at the electronic tutorial administration.
We will hand out an exercise sheet every week, the solutions for which have to be handed in per electronic email by Saturday 23h00 of the same week. The results will be discussed in the tutorial session on Monday of the following week (i.e. only one week later!), to ensure you get timely feedback.
The written exam will take place on Friday February 5th 14h00  16h00 in INF 308 HS 1.
The results of the exams can be reviewed (Klausureinsicht) on Tuesday 16 February 13h0014h00 in INF 227 (KIP) / SR 3.404, i.e. the usual lecture room this term.
Prerequisite knowledge
On the statistics side, there is no prerequisite knowledge, and we will (briefly) repeat the basic principles of statistics. On the particle physics side, the PEP5 lecture is sufficient. However, it appears to us that our lecture would be a natural followup on the Particle Physics lecture.
Lectures
12.10.2015  Lecture 1  Overview + goals of the lecture course; Introduction to basic statistical tools  
19.10.2015  Lecture 2  Formal introduction to probability, Conditional probabilities, Bayes' theorem, Frequentist and Bayesian interpretation  
26.10.2015  Lecture 3  Probability density (PD) functions, fundamental PDs, usefultoknow PDs.  
2.11.2015  Lecture 4  Central limit theorem (CLT), statistical and systematic uncertainties, propagation of uncertainties, combination of uncorrelated measurements  
9.11.2015  Lecture 5  The Monte Carlo (MC) method, MC integration, MC simulation, generation of random numbers in [0,1] or distributed according to a PD  
16.11.2015  Lecture 6  Applications of MC simulation in HEP: event generation and detector simulation; Estimators and their properties  
23.11.2015  Lecture 7  Simple estimators for the mean and variance. The maximum likelihood (ML) method as an estimator, variance of ML estimators with the analytical and graphical methods  
30.11.2015  Lecture 8  Variance of ML estimators with the MC method, combining measurements with ML, extended ML method, ML with binned data  
7.12.2015  Lecture 9  Connection between ML and Bayesian statistics, connection between ML and least squares methods. Hypothesis testing: goodnessoffit test with Pearson's χ² and KolmogorovSmirnov  
14.12.2015  Lecture 10  Terminology of hypothesis testing, example using particle ID, NeymanPearson lemma, contructing a test statistic, significance of an observed signal using a Posson RV example  
21.12.2015  Lecture 11  Confidence intervals and limits: Neyman construction, limits near a physical boundary, Feldman and Cousins limit construction, expected and observed limits  
4.1.2016  NO lecture 
Two papers on the CLs method to read instead: A.L. Read, "Modified frequentist analysis of search results (the CLs method)" CERN open2000205 (+ optional followup "Presentation of search results: the CLs technique", J. Phys. G: Nucl. Part. Phys. 28 2693 (2002)); G. Aad (ATLAS Collaboration), "Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC", Phys. Lett. B, 716 1 (2012). You can download the papers through the University's network, to use the journal subscription. 

11.1.2016  Lecture 12  Multivariate analysis (MVA) techniques and their application in particle physics: linear Fisher discriminant, neural networks  
18.1.2016  Lecture 13  Unfolding techniques: binbybin unfolding, regularised unfolding, iterative unfolding  
25.1.2016  Lecture 14  Decision trees and boosted decison trees as MVA techniques, brief summary of the CLs method 
Exercise sheets
 sheet 01
 sheet 02
 sheet 03
 sheet 04
 sheet 05
 sheet 06
 sheet 07
 sheet 08
 sheet 09
 sheet 10
 sheet 11
 sheet 12
Practice groups
 Group Tutorial (Dr. Veit Scharf)
14 participants
INF 227 / CIP Pool KIP 1.401, Mon 16:00  18:00