Martin Luther University Halle-Wittenberg

Further settings

Login for editors

Teaching

Statistics in economics

The main task of statistics is the planning and implementation of surveys as well as the preparation, evaluation, presentation and interpretation of empirical data. For this purpose, it uses mathematical models as well as techniques and procedures of computer science and mathematics. In terms of its methodology, statistics belongs to the high-tech disciplines and requires the ability to think analytically and to recognize correlations.

Statistical methods are used in a variety of applications in business, technology, science and research (e.g. market and opinion research, political and management consulting, banking and insurance, auditing, logistics, medical and pharmaceutical research and quality management).

Statistics in bachelor studies

The goal of statistics training in the bachelor's program is the acquisition of skills that enable the meaningful application of statistical methodology, but also a targeted descriptive or inferential evaluation and presentation of empirical data sets. In addition to the training in statistics, essential skills in mathematics are also taught. The careful teaching of fundamentals creates long-term key qualifications.

You will need the contents of the subject – even if you do not take a seminar or write a bachelor thesis in the field of statistics – in your bachelor studies wherever the interpretation of empirically collected data plays a role. Behind the ifo business climate index, for example, there are just as many statistics as behind the definition of poverty in industrialized nations. And market and opinion research is just as dependent on statistics as quality management in production.

Within the bachelor program we offer two basic modules on descriptive (Statistics I) and conclusive (Statistics II) statistics.

In addition, a bachelor seminar is held regularly in the winter term. Finally, we also supervise bachelor theses at the chair of statistics. As well the participation in the seminar as the supervision of the bachelor thesis requires participation in the allocation procedure of the economics department.

Statistics in master studies

The goal of statistics training in the master's program is to teach concepts and methods for designing and implementation of own empirical investigations and to acquire skills in the appropriate presentation of the results of statistical analyses.

The training is characterized in particular by the deployment of mathematical-statistical methods, the use of modern information technologies for data analysis, interdisciplinary teamwork and intensive practical relevance through case study work.

In addition to strong problem-solving skills in practice, graduates also acquire ethical competencies (data protection, protection of the interests of the test subjects) as well as the qualification for scientific work and improve their communication skills.

Methods subjects are anchored – subject-specifically with varying proportions – in all master's degree programs of the economics department. Wherever empirical investigations in the broadest sense are relevant, methods of statistics form the basis of work. Some examples are risk assessments and evaluations, be it for securities or for airport security, market research, the poverty and wealth reporting of the federal and state governments, the survey of employee or patient satisfaction, the evaluation of the effectiveness of didactic measures or the estimation of the costs of child care in public institutions.

Within the master program, we offer five modules that build on a basic knowledge of statistics (Statistics I and Statistics II or equivalent modules offered by other faculties or universities at bachelor`s level). Depending on the methods taught in the modules and their typical areas of application, the modules are assigned to different master's programs of the economics department.

Data collection techniques are required for the scientifically reliable implementation of surveys, but also of observational studies or experiments (module Sampling and Survey Design).

The evaluation of the data sets collected in this way is carried out – in addition to basic evaluations as already learned in Statistics I and Statistics II – mostly by means of so-called multivariate statistical analyses (taught in the module of the same name) such as factor or cluster analyses.

The process of data management, statistical analysis, interpretation of results, oral and written presentation and documentation of results, as is common in project work, is run through in the module Statistical Applications.

Construction procedures for statistical estimators and hypothesis tests as well as the mathematical-statistical properties of the procedures constructed in this way are the content of the module Statistical Tests and Estimators.

The module R-Tutorial is not assigned to any course of study and represents an additional offer of the chair of statistics that can be taken up voluntarily. It teaches the use of the statistical software R, which is used in almost all modules described above.

And of course, the chair of statistics also supervises master theses.

Up