Lecture on Data Analysis
Part of the courses physics master and computing and simulation in science.
Please refer to the modul-description (Ma.Phys/CSIS) for the contents.
Please register to the lecture on Wusel! See this HowTo
Lecture (2SWS, Wusel): Mon 10 c.t., F.13.15
Exercise (2SWS, Wusel): Wed 14:15, D.11.03
CORONA-Update: we will start with the lecture on 20.4.2020 via zoom.
Contents:
- Uncertainty and interpretation of measurements (20.04.2020)
- Description of data
- PDFs (27.04.2020)
- Estimator (04.05.2020)
- Error propagation
- Fitting data
- Bayesian Probability (11.05.2020)
- Interval estimation (18.05.2020)
- Hypothesis-tests (25.05.2020)
- Monte Carlo and random numbers (08.06.2020)
- Resampleing methods (15.06.2020)
- Unfolding
- Multivariate analysis technics (22.06.2020)
- Boosted Decision Trees
- Likelihood, k-NN and Support Vector Machines (29.06.2020)
- Neural Networks (06.07.2020)
- Deep Learning (13.07.2020)
Exercises:
Date
Sheet
Material
22.04.2020
covariance.txt, hist.txt , example_simple.py
29.04.2020
06.05.2020
13.05.2020
20.05.2020
MLE.txt, FC-example.C, FeldmanCousins.py
27.05.2020
03.06.2020
10.06.2020
17.06.2020
24.06.2020
01.07.2020
08.07.2020
Literature:
Glen Cowan, "Statistical Data Analysis", BUW-Bib, web-page
Roger Barlow, "Statistics: a guide to the use of statistical methods in the physical sciences", BUW-Bib
Olaf Behnke et al., "Data analysis in high energy physics: a practical guide to statistical methods", BUW-Bib, BUW online-edition
Martin Erdmann et al., "Statistische Methoden in der Experimentalphysik", BUW-Bib
Frederick James, "Statistical methods in experimental physics", BUW-Bib