SoSe 26: Module offerings

• Einführung in die Statistik (Introduction to Statistics)

  0171cA1.5
  learning objectives: Students gain basic knowledge of information reduction when dealing with one-dimensional and multidimensional data on ... read more

  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
  
  workload
  180 hours (6 ECTS)
  
  duration / frequency
  one semester / every summer semester

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  • 10120401 Lecture
    Introduction to Statistics (V) (Ulrich Schneider)
    Schedule: Mo 14:00-16:00 (Class starts on: 2026-04-13)
    Location: HFB/A Hörsaal, Hs 101 Hörsaal
    
  • 10120402 Practice seminar
    Introduction to Statistics (Ü) (Ulrich Schneider)
    Schedule: Mi 14:00-16:00 (Class starts on: 2026-04-15)
    Location: HFB/A Hörsaal (Garystr. 35-37)
    
  • 10120405 Tutorial
    Introduction to Statistics (T) (Tutor*innen)
    Schedule: -
    Location: keine Angabe
    

• Sampling Methods

  0171cB2.5
  learning objectives: Students gain an introduction into the field of survey statistics and learn the basic methods of sampling theory. ... read more

  learning objectives:
  Students gain an introduction into the field of survey statistics and learn the basic methods of sampling theory. They also learn about the most important sampling techniques and how to use them. In addition, they use example cases to learn how to deal with nonreponse and how to use calibration methods. In the tutorial section, students learn how statistics software can be used to draw samples, for example, from the Campus-Files from the Federal Statistical Office. They also learn the relevant methods and are thus able to assess critically the practical implementations of sampling procedures. Moreover, they learn to explain and evaluate survey data generated through polling. The module takes into consideration gender and diversity to establish conditions that make it possible for all students to participate.
  
  

  course content:
  Population and sampling probabilities, Simple random sampling, Stratified sampling, Cluster sampling, Two-stage (multi-stage) sampling, Selection schemes with unequal probabilities, Regression estimation
  
  

  language of instruction:
  German / English
  
  workload
  180 hours (6 ECTS)
  
  duration / frequency
  one semester / irregular

  close
  • 10122001 Lecture
    Machine Learning (Philipp Bach)
    Schedule: Mi 14:00-17:00 (Class starts on: 2026-04-22)
    Location: Hs 103 Hörsaal (Garystr. 21)
    
  • 10122026 Methods Tutorial
    Machine Learning (Philipp Bach)
    Schedule: Mi 17:00-18:00 (Class starts on: 2026-04-22)
    Location: Hs 103 Hörsaal (Garystr. 21)
    

• Modules w/o courses in this semester

  4 Modules
  • Mathematics (for Students of Business and Economics) 0171cA1.4
  • Schließende Statistik (Inferential Statistics) 0171cA1.6
  • Einführung in die Ökonometrie (Introduction to Econometrics) 0171cB2.1
  • Statistische Modellierung (Statistical Modeling) 0171cB2.2