Teaching overview

Bachelor

Mathematik

Mathematik
Introductory “Mathematics 101” course covering the basics of: analysis, elementary financial mathematics, linear algebra, probability calculus.

Statistische Modellbildung

Statistische Modellbildung
Statistical modeling course consolidating and extending the skills for exploratory and model-based analyses: Multivariate methods, cluster analysis, independence tests, (generalized) linear models.

Master

Time Series Analysis

Time Series Analysis
Methods course for the analysis and modeling of time series data: Stochastic processes, ARIMA models, stationarity, unit roots, GARCH models, time series regression and structural change.

Microeconometrics

Microeconometrics
Methods course for the analysis and modeling of cross-sectional data: Generalized linear models, binary/multinomial/ordered responses, count data, limited dependent variables, duration models.

PhD

R Programming

R Programming
Advanced R programming course for statistical models: Model formulation, object orientation and formula interfaces, documentation/packaging/version control, numeric optimization, inference.

Extracurricular

R Introduction

R Introduction
Introductory R course: First steps, installation/documentation/usage, data management, exploratory data analysis and regression, graphics and statistical reports.

Applied Econometrics with R

Applied Econometrics with R
Course materials accompanying the “Applied Econometrics with R” book (Kleiber & Zeileis 2008): Linear regression, diagnostics, microeconometrics, time series, programming basics, financial econometrics.