Module offerings
Statistics (30 cp) study regulations of wintersemester 2016/17)
0191c_m30-
Mathematics (for Students of Business and Economics)
0171cA1.4learning objectives:
Students learn the essential mathematical methods they need in order to understand the formalized economic relationships that they will encounter during their studies. The methods will also enable them to develop solutions to problems related to these economic relationships. The methods include a fundamental understanding of linear algebra and analysis as well as how to apply that to economic problems. In addition, the module treats the students’ individual and cultural diversity as a positive contribution that supports student and teacher success.
course content:
Vectors, matrices, determinants, linear systems of equations, functions of one or more variables, ordinary and partial derivatives, extreme values of functions with and without constraints, integral calculus.
types of course units / workload per unit / obligatory or optional participation
Vorlesung / 3 SWS / Teilnahme wird empfohlen
Übung / 1 SWS / Teilnahme wird empfohlen
Studentisches Tutorium / - SWS / Teilnahme wird empfohlentest
Klausur (ca. 120 Minuten)language of instruction:
close
German
workload
180 hours (6 ECTS)
duration / frequency
one semester / every winter semester-
10120301
Lecture
Mathematics for Economists (V) (Ulrich Schneider)
Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-14)
Location: Hs 101 Hörsaal (Garystr. 21)
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10120302
Practice seminar
Mathematics for Economists (Ü) (Ulrich Schneider)
Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
Location: Hs 101 Hörsaal (Garystr. 21)
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10120305
Tutorial
Mathematics for Economists (T) (Tutor*innen)
Schedule: Mi 08:00-18:00 (Class starts on: 2024-10-16)
Location: div. Hörsäle
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10120301
Lecture
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Schließende Statistik (Inferential Statistics)
0171cA1.6learning objectives:
Students learn to make decisions based on statistical data and assess the quality of these decisions. They learn how to solve three central types of statistical problems: Estimating unknown parameters of a distribution (point estimation), determining the confidence interval for an unknown parameter (confidence interval), making statements about the equality or inequality of distributions (tests). Students learn to apply these techniques themselves using empirical data and with the help of computer technology. The diversity of perspectives, experiences, and skills that the students bring with them to the group is treated as a positive contribution to the quality of research they produce and entails great benefits.
course content:
Continuous distribution models, sampling functions, parameter estimation, confidence intervals, hypothesis testing, regression analysis.
types of course units / workload per unit / obligatory or optional participation
Vorlesung / 2 SWS / Teilnahme wird empfohlen
Übung / 1 SWS / Teilnahme wird empfohlen
Studentisches Tutorium / - SWS / Teilnahme wird empfohlentest
Klausur (ca. 120 min.)language of instruction:
close
German / English
workload
180 hours (6 ECTS)
duration / frequency
one semester / every winter semester-
10120501
Lecture
Inferential Statistics (V) (Ulrich Schneider)
Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-14)
Location: HFB/A Hörsaal (Garystr. 35-37)
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10120502
Practice seminar
Inferential Statistics (T) (Nicolas Frink)
Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
Location: HFB/C Hörsaal (Garystr. 35-37)
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10120505
Tutorial
Inferential Statistics (T) (Tutor*innen)
Schedule: Mo 08:00-14:00 (Class starts on: 2024-10-14)
Location: keine Angabe
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10120501
Lecture
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Statistische Modellierung (Statistical Modeling)
0171cB2.2learning objectives:
Students are advised to take “Introduction to Econometrics” before starting this module. Students learn how to analyze data for which the regression model is not appropriate. Students deal with the most important models used in the analysis of nominal, ordinal, and integer characteristics so that they can describe the models and also apply them empirically. Students will continue to discuss the analysis of general dependency patterns. They also learn the relevant methods and how to interpret the results obtained through use of these methods. In the tutorial section, students learn how to use the appropriate software and interpret the results based on examples. Everyone is given an equal opportunity to contribute their ideas and concepts.
course content:
Logit and probit models, threshold models, cumulative probit models, count data models, generalized linear model, log-linear model, models for longitudinal data.
language of instruction:
close
German / English
workload
180 hours (6 ECTS)
duration / frequency
one semester / irregular-
10121301
Lecture
Statistical Modeling (V) (Ulrich Schneider)
Schedule: Mo 16:00-18:00 (Class starts on: 2024-10-14)
Location: HFB/D Hörsaal (Garystr. 35-37)
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10121326
Methods Tutorial
Statistical Modeling (Ü) (Lukas Fink)
Schedule: Mi 16:00-18:00 (Class starts on: 2024-10-30)
Location: Hs 105 Hörsaal (Garystr. 21)
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10121301
Lecture
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Einführung in die Statistik (Introduction to Statistics) 0171cA1.5
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Einführung in die Ökonometrie (Introduction to Econometrics) 0171cB2.1
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Sampling Methods 0171cB2.5
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