## Statistical Methods for Data Analysis

The lecture Statistical Methods for Data Analysis is divided into two parts.

Nowadays, data is usually collected electronically in huge amounts. The students learn the appropriate handling of statistical methods for the analysis of moderate to very large amounts of data, oriented to the temporal sequence of a data analysis. The exercises are solved (also) on the computer using common software. In the course, practical and theoretical competence in data analysis is acquired for the preparation of theses and later professional practice.

The course contents include:

**SMD A: **Numerical methods of data processing, data handling and programming, algorithms and data structures, methods of linear algebra, probability theory, one and multi-dimensional distributions, random numbers and Monte Carlo methods, data mining methods: Discriminant Analysis, Principal Component Analysis, Feature Selection, Supervised Learning (kNN, Decision Trees, Random Forests), MRMR, Unsupervised Learning (Ensemble Learner), Convolutional Neural Nets.

**SMD B: **Parameter estimation, optimisation problems, least squares method, maximum likelihood method, numerical fit methods, regularisation, confidence intervals and hypothesis testing, parameterisation of data, Bayesian methods, methods for solving inverse problems, validation techniques, treatment of systematic errors, acceptance calculation.

## Astroparticle Physics

The students learn contents from the border area between astronomy, nuclear and particle physics and cosmology and their interdisciplinary discussion. They also learn argumentation techniques based on the interaction of theory and experiment. Phenomenological calculations are used to learn how to plan and check the scope of experiments.

**The learning contents are:**

Cosmic rays: nuclei, electrons, photons, neutrinos, detection of energetic particles, acceleration mechanisms, propagation of particles through the interstellar medium, interaction and decay, galactic magnetic fields, cosmic background radiation, infrared background, cosmological aspects, star and galaxy formation.

Astrophysical sources: Remnants of stellar explosions, compact objects (black holes, neutron stars), shock waves in the ejected stellar envelope, molecular clouds, starburst galaxies,galaxy clusters, supernovae, binary systems, microquasars, nuclei of active galaxies, gamma ray bursts.

Particle-physical sources: Spallation, dark matter (WIMPs), topological defects, monopoles, proton decay, axions,

Particle physics measurements: including effective cross sections, energy loss in the medium, neutrino oscillations, physics at highest energies.

Detection instruments: optical telescopes, radio telescopes, air shower systems, gamma-ray telescopes, neutrino telescopes, satellite experiments, low energy detectors.

Practical consequences: biological effects, technological consequences

### Search & People Search

### Location & approach

The campus of the Technical University of Dortmund is located near the freeway junction Dortmund West, where the Sauerland line A45 crosses the Ruhr expressway B1/A40. The Dortmund-Eichlinghofen exit on the A45 leads to the South Campus, the Dortmund-Dorstfeld exit on the A40 leads to the North Campus. The university is signposted at both exits.

The "Dortmund Universität" S-Bahn station is located directly on the North Campus. From there, the S-Bahn line S1 runs every 20 or 30 minutes to Dortmund main station and in the opposite direction to Düsseldorf main station via Bochum, Essen and Duisburg. In addition, the university can be reached by bus lines 445, 447 and 462. Timetable information can be found on the homepage of the Rhine-Ruhr transport association, and DSW21 also offer an interactive route network map.

One of the landmarks of the TU Dortmund is the H-Bahn. Line 1 runs every 10 minutes between Dortmund Eichlinghofen and the Technology Center via Campus South and Dortmund University S, while Line 2 commutes every 5 minutes between Campus North and Campus South. It covers this distance in two minutes.