Course descriptions: Undergraduate

Statistics for Undergraduate/Bachelor Programme

Representative: Prof. Dr. Timo Schmid

Subject Topics:

The lectures in statsical methods are offered in two parts and are examined separately. Statistical Methods I (descriptive statistics, ger: "Methoden der Statistik I") and Statistical Methods II (inferential statistics, ger: "Methoden der Statistik II") are held every semester by the Chair of Statistics and Econometrics. Within the scope of the lectures Statistical Methods I and II as well as the corresponding exercises, the most important basics and methods of descriptive statistics, probability theory and inductive statistics as well as the implementation of these methods in modern statistical software (R-Studio) are taught.

The section on descriptive statistics (Statistical Methods I) covers methods with which given data can be presented in a manageable way or characterised by meaningful numbers such as location parameters, measures of dispersion or correlation coefficients. Finally, various questions of data collection are addressed, because a statistical method, no matter how sophisticated, is only as good as the data on which it is applied. In addition, the course Statistical Methods I deals with the basic concepts, rules and regularities of probability theory, whereby the main focus of interest is on random processes that can be described by so-called random variables. Many variables known from descriptive statistics, such as the distribution parameters, can be defined analogously for random variables. In addition, the law of large numbers and the central limit theorem, two theorems of probability theory that are particularly important for inductive statistics, are introduced. In the further part of inductive statistics (Statistical Methods II), the emphasis is on methods which allow probability theory based conclusions to be drawn from a sample to a population. Building on the previously discussed basics of probability theory, methods of point estimation and interval estimation as well as important hypothesis tests are dealt with. This is followed by an overview of some other interesting sub-areas of statistics, with the methods of regression in particular being discussed in detail. The statistics package R-Studio is used in both courses. This statistics software is available free of charge via the Internet and features the latest statistical methods. A worldwide community of method developers ensures constant updates of R-Studio.

Building on the courses Statistical Methods I and II, the course Statistical Modelling intensively discusses regression models for metric variables. Subsequently, the most important models in the analysis of binary (e.g. unemployed yes/no), nominal (e.g. highest school-leaving qualification) or integer characteristics are dealt with and generalised regression models are introduced. The students study the corresponding methods and are enabled to interpret results based on these methods in a meaningful way. In the exercise part, the use of corresponding software (R-Studio) is further developed and the results obtained are interpreted using examples. 

Objectives:

Students should familiarise themselves with the fundamental statistical methods. In particular, the theoretical basic concepts, the preconditions of their applicability, their implementation implementation by means of statistical software as well as the reasonable interpretation of the results present the key aspects of these methods. 

Syllabi (descriptions of the modules):

Statistical Methods I(134.4 KB)

Statistical Methods II(135.1 KB)

Statistical Modelling(366.4 KB)

Exam:

A 90-minute written exam is offered each semester for the "Statistical Methods I" and the "Statistical Methods II" courses. A 120-minute written exam is offered every semester for the course "Statistical Modelling". There is a written exam offered for the three courses in each semester. This also applies if the course is not being lectured in the respective semester.

Bachelor Degree Programme with beginning in winter term 2010/2011

* The course EES has different ECTS points!

** Deviations possible!