In statistics, we are used to search for the best predictors of some random variable. In many situations, however, we are interested in predicting a system's behavior under manipulations. For such an analysis, we require knowledge about the underlying causal structure of the system. In this course, we study concepts and theory behind causal inference.

The course introduces applied statistical methods as used in current research in environmental sciences. Students learn to analyse data sets using the R software package, critically interpret results and assess the suitability of statistical methods for different questions.

Regression studies the dependence of a random response variable on other variables. We consider the theory and application of linear regression with one or more covariates. Various extensions such as nonlinear models, generalized linear models, nonparametric models, robust methods, and model selection are discussed.

In regression, the dependency of a random response variable on other variables is examined. We consider the theory of linear regression with one or more covariates, high-dimensional linear models, nonlinear models and generalized linear models, model choice and nonparametric models. Several numerical examples will illustrate the theory.

Introduction to basic methods and fundamental concepts of statistics and probability theory for non-mathematicians. The concepts are presented on the basis of some descriptive examples.

Vertiefung von Statistikmethoden. Nach dem detailierten Fundament aus Statistik I liegt nun der Fokus auf konzeptueller Breite und konkreter Problemlösungsfähigkeit mit der Statistiksoftware R.

"Statistics Lab" is an Applied Statistics Workshop in Data Analysis. It provides a learning environment in a realistic setting.Students lead a regular consulting session at the Seminar für Statistik (SfS). After the session, the statistical data analysis is carried out and a written report and results are presented to the client. The project is also presented in the course's seminar.

Introduction to basic methods and fundamental concepts of statistics andprobability theory for non-mathematicians. The concepts are presented onthe basis of some descriptive examples. The course will be based on thebook "Statistics for research" by S. Dowdy et.al. and on thebook "Introductory Statistics with R" by P. Dalgaard.