4020215094 Statistical Methods of Data Analysis
Digital- & Präsenz-basierter Kurs
- classroom language
- DE
- aims
- - General introduction to probability theory
- Probability densities and random variables
- Statistical test of hypotheses and significance
- parameter estimates, confidence intervals and limits
- unfolding
- classification and statistical learning
- structure / topics / contents
- Statistical methods for data analysis in particle and astrophysics will be discussed. These methods are necessary to interpret experimental results and compare them to theory. More advanced topics (such as machine learning and unfolding) will also be introduced.
This course investigates the theoretical motivations and teaches practical computational implementation using python or C++.
Problem sets will be derived from recent developments in elementary physics and astrophysics.
- assigned modules
-
P25.1.c
- amount, credit points; Exam / major course assessment
- 3 SWS, 6 SP/ECTS (Arbeitsanteil im Modul für diese Lehrveranstaltung, nicht verbindlich)
written or oral exam.
- other
- The lecture and problem class are likely to be hold in person. The course will be held in English.
- contact
- Timothée Theveneaux-Pelzer (tpelzer@physik.hu-berlin.de)
- Moodle link:
- http://moodle.hu-berlin.de/course/view.php?id=107641