Introductory “Mathematics 101” course covering the basics of: Analysis, elementary financial mathematics, linear algebra, probability calculus.
Statistical modeling course consolidating and extending the skills for exploratory and model-based analyses: Multivariate methods, cluster analysis, independence tests, (generalized) linear models.
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.
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.
Advanced R programming course for statistical models: Model formulation, object orientation and formula interfaces, documentation/packaging/version control, numeric optimization, inference.
Introductory R course: First steps, installation/documentation/usage, data management, exploratory data analysis and regression, graphics and statistical reports.
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.