SoSe 21: Module offerings

Statistics

0191d_m30
• Einführung in die Statistik (Introduction to Statistics)

0171dA1.6

learning objectives:
Students gain basic knowledge of information reduction when dealing with one-dimensional and multidimensional data on different measurement levels (“descriptive statistics”). Students also learn how to use the tools of probability theory to deal with the randomness of statistical information. Based on the concept of probability, students learn to derive the concept of random variables. In addition to learning about basic concepts and definitions, students also learn how to describe important distribution models. Students also use software to display central statistical concepts, such as the dispersion of results within a distribution model. They learn to process simple statistical analyses themselves using a computer. The module integrates intercultural and international diversity as a cross-sectional topic that students should be aware of when it comes to research methods and evaluations.

course content:
One-dimensional and multidimensional empirical distribution, principles of probability theory, random variables, ratios and indices, discrete distribution models.

language of instruction:
German/English

180 hours (6 ECTS)

duration / frequency

one semester / every summer semester

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• 10120401 Lecture
Introduction to Statistics (V) (Jan Pablo Burgard)
Schedule: Di 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2021-04-13)
Location: Online - zeitABhängig
• 10120402 Practice seminar
Introduction to Statistics (Ü) (Jan Pablo Burgard)
Schedule: Mi 12:00-14:00 (Class starts on: 2021-04-14)
Location: Online - zeitUNabhängig
• 10120405 Tutorial
Einführung in die Statistik (T) (N.N.)
Schedule: Mi 08:00-10:00 (Class starts on: 2021-04-14)
Location: Online - zeitABhängig
• Einführung in die Ökonometrie (Introduction to Econometrics)

0171dB2.1

learning objectives:
Students learn to quantify and verify economic behavioral equations using statistical methods and observational data. They learn to describe and apply the basic methods of regression analysis including testing parameters. Through a trained understanding of econometric models, they can also identify the effects of deviating or violating models on estimates and regression parameter tests and develop appropriate strategic solutions. By including a practical computational exercise, students learn to perform regression analyses by themselves and interpret the results appropriately. Another important objective is to use student diversity as a resource and make a conscious effort to include it in the students’ daily life.

course content:
Fundamental methods of econometrics, for example: The classical linear regression model, parameter estimation with the least squares method, confidence ranges and parameter tests, modeling structural breaks and season, heteroscedasticity, and autocorrelation of residuals.

language of instruction:
German / English

180 hours (6 ECTS)

duration / frequency

one semester / irregular

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• 10121201 Lecture
Introduction to Econometrics (V) (Dieter Nautz)
Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2021-04-12)
Location: Online - zeitUNabhängig
• 10121202 Practice seminar
Introduction to Econometrics (Ü) (Lea Sieckmann)
Schedule: Fr 14:00-16:00 (Class starts on: 2021-04-16)
Location: Online - zeitUNabhängig
• 10121205 Tutorial
Introduction to Econometrics (T) (Lea Sieckmann)
Schedule: Mi 12:00-14:00 (Class starts on: 2021-04-14)
Location: Online - zeitABhängig
• 10121205a Tutorial
Einführung in die Ökonometrie (T) (Lea Sieckmann)
Schedule: Mi 16:00-18:00 (Class starts on: 2021-04-14)
Location: Online - zeitABhängig
• 10121205b Tutorial
Einführung in die Ökonometrie (T) (Lea Sieckmann)
Schedule: Do 12:00-14:00 (Class starts on: 2021-04-15)
Location: Do Hs 102 Hörsaal (Garystr. 21), Do Online - zeitABhängig
• 10121205c Tutorial
Einführung in die Ökonometrie (T) (Lea Sieckmann)
Schedule: Do 14:00-16:00 (Class starts on: 2021-04-15)
Location: Do Hs 102 Hörsaal (Garystr. 21), Do Online - zeitABhängig
• Mathematik für Wirtschaftswissenschaftler (Mathematics for Economists) 0171dA1.5
• Schließende Statistik (Inferential Statistics) 0171dA1.7
• Statistische Modellierung (Statistical Modeling) 0171dB2.2
• Stichprobenverfahren (Sampling Procedure) 0171dB2.5