Module 31-M-ASM2 Advanced Statistical Methods II

Non-official translation of the module descriptions. Only the German version is legally binding.

Students acquire advanced skills of theory and application of statistical methods in a range of application areas.

The goal of this module is to acquire competences for the specification, estimation and simulation of empirically validated models. The focus of quantitative methods in economics lies on the provision and analysis of data based on an underlying economical research question, where typically the numerical application of methods is in the center of attention. Students learn to use statistical and econometrical models as a method to extract information from the growing amount of data. Hereby a special emphasis is given to acquire competences in the usage of generally applicable modeling paradigms and methods in order to allow for a widespread application to a large number of application areas.

Moreover students can include courses of other faculties (e.g. Fakultät für Mathematik oder Physik) of the Bielefeld university into this module which allows them to acquire a high level of interdiscplinary competences including the competence to work in an interdisciplinary context. Thus student develop beside statistical competences also social and communication skills.

In this module students acquire advanced competences in the area of statistical modeling and/or in methodologically linked areas such as mathematical statistics or statistical physics. The content of this module consists in statistical or methododologically linked research questions, including structural issues, scientific tools and methods.

The courses included in this module in the area of statistics discuss data analytic and data base oriented methods and models. The courses extend material acquired in introductory courses and offer insights into the areas that also qualify for a deeper understanding of the methods.

This module contains a long list of courses, some of which are only read infrequently.

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