Statistical Methods in Physics
7.5 credits cr.
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How do we learn from experimental data in a proper way? In this course, you will learn the concepts of probability theory and statistical inference used to interpret experimental data. You will address the problems both from a theoretical perspective and with practical labs.
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Making progress in science depends on our ability to obtain meaningful and reliable insights into experimental data. In this course, you will learn about insightful data analysis via statistical inference. The course provides an overview of the concepts of probability theory and the extraction of knowledge from measurements or observation. You will learn how to robustly extract information from uncertain observations, e.g. the separation of signals from backgrounds in particle or astrophysical applications. The course discusses various approaches to statistical data analysis, ranging from the “Maximum Likelihood” and the “Least Square” methods to Markov Chain Monte Carlo techniques. The course will provide a thorough epistemological background by covering major topics of statistical analyses such as estimation, confidence intervals, covariance matrices, hypothesis testing and the detection of signals, the treatment of systematic and stochastic uncertainties. The course will be accompanied by a practical lab.
If you want to learn more after this course, the course "Physical Measurement Techniques" is recommended as a continuation.
Teaching during the spring semester 2021
During the spring semester 2021, lectures, tutorials and computer lab works will be done remotely. The course is examined through homework problems, reports on computer labs, and a remote oral exam. The course is using the Athena learning platform.
This is a second cycle course given at half speed during daytime. This course can also be taken as a third cycle course.
The teaching consists of lectures, group education, exercises and practical labs.
The course is examined through written and oral examinations and lab reports.
ScheduleThe schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
Course literatureNote that the course literature can be changed up to two months before the start of the course.
- "Statistical data Analysis" by Glen Cowan, Oxford Science Publications, Clarendon Press, Oxford 1998
- "Statistical Methods in experimental physics", 2nd edition, Fred James, World Scientific Publishing, ISBN-13 978-981-256-795-6
Här ligger ett skript.
Laboratory supervisor and exercises:
Vasile Cristian Antochi, e-mail: email@example.com
Academic advisor at the Department of Physics: firstname.lastname@example.org
Student office: email@example.com