Module: Quantitative Methods 2 (5202-070)

Persons:

• HonProfDr Ulrich Scheurle (verantwortlich)

Degree Program:

• Business Administration and Economics (Bachelor, since 28.07.2010)
  2. Semester, compulsory
• Business Administration and Economics Vocational and Business Education (Bachelor, since 28.07.2010)
  2. Semester, compulsory
• Business Administration and Economics (Bachelor, since 01.10.2015)
  2. Semester, compulsory
• Education for Business and Economics (Bachelor, since 01.10.2015)
  2. Semester, compulsory
• Business Administration and Economics (Bachelor, since 01.10.2017)
  2. Semester, compulsory
• Education for Business and Economics (Bachelor, since 01.10.2015)
  2. Semester, compulsory
• Education for Business and Economics (Bachelor, since 01.10.2018)
  2. Semester, compulsory

Sprache:

German

ECTS:

6 credits

Frequency:

every summer semester

Length of the Module:

1 semester

Module examination:

Die Modulprüfung "Quantitative Methoden 2" erfolgt in Form einer Klausur, die sich aus den Teilleistungen "Mathematik für Wirtschaftswissenschaftler 2" und "Statistik 1" zusammensetzt. Die Modulprüfung ist nur dann bestanden, wenn beide Teilleistungen "Mathematik für Wirtschaftswissenschaftler 2" und "Statistik 1" jeweils mindestens mit "bestanden" (jeweils mindestens mit 19 Punkte) bewertet wurden und die sich daraus ergebende Modulnote mindestens "ausreichend" (4,0) ist.

Final examination:

written exam (50% Mathematics for Economists 2, 50% Statistics 1)

Length of the examination:

90 minutes

Workload:

180 hours 84 hours class attendance 120 hours preparation and follow-up, preparation for the exam and exam

Professional competences:

The students know and understand basic mathematical and statistical methods. They master basic approaches of financial mathematics, linear algebra and linear optimisation. They know and understand approaches of basic statistical data preparation and descriptive data analysis. They are familiar with the basics of probability theory as well as the concept of random variables and their distribution. The can apply these mathematial and statistical concepts and methods to economic and socio-economic objects of study. They are able to interpret the solutions generated with these methods and to evaluate them critically.

Courses