SoSe 20: Module offerings
Econometrics (30 cp) (study regulations of wintersemester 2016/17)
0190c_m30-
Einführung in die Statistik (Introduction to Statistics)
0171cA1.5learning 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:
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German/English
workload
180 hours (6 ECTS)
duration / frequency
one semester / every summer semester-
102010
Lecture
Statistik for Economics (V) (Timo Schmid)
Schedule: Mi 12:00-14:00 (Class starts on: 2020-04-15)
Location: Onlinelehre - zeitUNabhängig
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102011
Practice seminar
Statistics for Economics (Ü) (Sylvia Harmening)
Schedule: Di 10:00-12:00 (Class starts on: 2020-04-21)
Location: Onlinelehre - zeitUNabhängig
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102012
Tutorial
Statistik für Wirtschaftswissenschaftler (T) (Sylvia Harmening)
Schedule: Mo 08:00-16:00 (Class starts on: 2020-04-20)
Location: Onlinelehre - zeitUNabhängig
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102010
Lecture
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Einführung in die Ökonometrie (Introduction to Econometrics)
0171cB2.1learning 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:
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German / English
workload
180 hours (6 ECTS)
duration / frequency
one semester / irregular-
102038
Lecture
Einführung in die Ökonometrie (V) (Dieter Nautz)
Schedule: Mo 10:00-12:00 (Class starts on: 2020-04-20)
Location: Hs 105 Hörsaal (Garystr. 21)
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102039
Methods Tutorial
Einführung in die Ökonometrie (Ü1) (Lea Sieckmann)
Schedule: Fr 12:00-14:00 (Class starts on: 2020-04-17)
Location: Hs 104a Hörsaal (Garystr. 21)
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102085
Practice seminar
Einführung in die Ökonometrie (Ü2)
Schedule: Di 12:00-14:00, Di 14:00-16:00, Mi 12:00-14:00, Mi 14:00-16:00, Do 12:00-14:00, Do 14:00-16:00 (Class starts on: 2020-04-14)
Location: K 006a PC Pool 1 (Garystr. 21)
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102038
Lecture
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Einführung in die Mikroökonometrie (Introduction to Microeconometrics)
0171cB2.4-
102072
Lecture
Einführung in die Mikroökonometrie (V) (Viktor Steiner)
Schedule: Di 16:00-17:30 (Class starts on: 2020-04-21)
Location: Onlinelehre - zeitABhängig
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102073
Practice seminar
Einführung in die Mikroökonometrie (Ü) (Astrid Pape)
Schedule: Mo 14:00-16:00 (Class starts on: 2020-04-20)
Location: K 006b PC-Pool 2 (Garystr. 21)
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102072
Lecture
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Mathematik für Wirtschaftswissenschaftler (Mathematics for Economists) 0171cA1.4
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Schließende Statistik (Inferential Statistics) 0171cA1.6
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Einführung in die Zeitreihenanalyse (Introduction to Time Series Analysis) 0171cB2.3
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