Statistics for Economists

A sound command of statistics is one of the basic prerequisites for a successful degree in economics and organizational sciences. Statistics that are particularly relevant for economists can be broadly divided into descriptive statistics and inferential statistics, with elementary principles of probability theory being indispensable for mastering inferential statistics. The key qualification objective of the module is, in addition to the secure application of various methods (regressions, tests, etc.), above all the ability to correctly interpret statistical results. Examples include questions about the actual explanatory power of regressions (e.g., using the coefficient of determination) or of tests (the problem of asymmetry in explanatory power when accepting versus rejecting hypotheses).

Statistics I

Building on the concept of statistical variables, Statistics I covers the fundamental topics of descriptive statistics. These include, among others, key measures of distributions, multivariate regression, and the description of time series. This is followed by elementary topics in probability theory, such as probability spaces and specific probability distributions.

Statistics II

Building on Statistics I, the focus initially lies on the most important limit theorems of statistics, which ultimately form the basis of statistical test theory. Test theory is an integral part of inferential statistics, and for the various hypothesis tests covered, particular emphasis is placed on the appropriate evaluation of test decisions, especially the discussion of Type I versus Type II errors.