402-0738-00L  Statistical Methods and Analysis Techniques in Experimental Physics

SemesterSpring Semester 2020
LecturersM. Donegà, C. Grab
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
402-0738-00 GStatistical Methods and Analysis Techniques in Experimental Physics5 hrs
Tue08:45-13:30HIT F 21 »
M. Donegà, C. Grab

Catalogue data

AbstractThis lecture gives an introduction to the statistical methods and the various analysis techniques applied in experimental particle physics. The exercises treat problems of general statistical topics; they also include hands-on analysis projects, where students perform independent analyses on their computer, based on real data from actual particle physics experiments.
ObjectiveStudents will learn the most important statistical methods used in experimental particle physics. They will acquire the necessary skills to analyse large data records in a statistically correct manner. Learning how to present scientific results in a professional manner and how to discuss them.
ContentTopics include:
- modern methods of statistical data analysis
- probability distributions, error analysis, simulation methos, hypothesis testing, confidence intervals, setting limits and introduction to multivariate methods.
- most examples are taken from particle physics.

Methodology:
- lectures about the statistical topics;
- common discussions of examples;
- exercises: specific exercises to practise the topics of the lectures;
- all students perform statistical calculations on (their) computers;
- students complete a full data analysis in teams (of two) over the second half of the course, using real data taken from particle physics experiments;
- at the end of the course, the students present their analysis results in a scientific presentation;
- all students are directly tutored by assistants in the classroom.
Lecture notes- Copies of all lectures are available on the web-site of the course.
- A scriptum of the lectures is also available to all students of the course.
Literature1) Statistics: A guide to the use of statistical medhods in the Physical Sciences, R.J.Barlow; Wiley Verlag .
2) J Statistical data analysis, G. Cowan, Oxford University Press; ISBN: 0198501552.
3) Statistische und numerische Methoden der Datenanalyse, V.Blobel und E.Lohrmann, Teubner Studienbuecher Verlag.
4) Data Analysis, a Bayesian Tutorial, D.S.Sivia with J.Skilling,
Oxford Science Publications.
Prerequisites / NoticeBasic knowlege of nuclear and particle physics are prerequisites.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits10 credits
ExaminersM. Donegà, C. Grab
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 30 minutes
Additional information on mode of examinationBased on the regulation of continuous performance assessments, students have to work on a project and present the results at the end of the semester. This additional task is graded on a pass/fail basis and students who fail this task have to repeat the complete course.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Science Education MasterSpec. Courses in Respective Subject with Educational FocusWInformation
High-Energy Physics (Joint Master with EP Paris)Optional Subjects in PhysicsWInformation
Physics TCSpecialized Courses in Respective Subject with Educational FocusWInformation
Physics Teaching DiplomaSpec. Courses in Resp. Subj. w/ Educ. Focus & Further Subj. DidacticsWInformation
Physics Teaching DiplomaCompulsory Elective CoursesWInformation
Physics MasterSelection: Particle PhysicsWInformation
Computational Science and Engineering BachelorElectivesWInformation
Computational Science and Engineering MasterElectivesWInformation