Universität Wien
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040772 UK Complex Statistical Methods (2019W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 03.10. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 10.10. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 17.10. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 24.10. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 31.10. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 07.11. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 14.11. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 21.11. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 28.11. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 05.12. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 12.12. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 09.01. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 16.01. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 23.01. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 30.01. 13:15 - 14:45 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

The course covers methods of data collection and data generation by simulation
Part 1: Basics of survey sampling, Model assisted survey sampling
Part 2: Methods of data cleaning and data integration
Part 3: Simulation and Markov Chain Monte Carlo Methods
Part 4: Statistical Applications of Markov Chain Monte Carlo methods

Assessment and permitted materials

Presentation of exercises during the semester
Midterm exam
Fibnal exam

Minimum requirements and assessment criteria

Attendence of the lectures (At most 3 units missing)
Presentation of exercises. For each Part there is one execise sheet. Each exrcise sheet counts for 30 point
Midterm exam about part 1 and part 2 (60 points)
Final exam about part 3 and part 4 (60 ppoints)
For positive assessment each of the parts must be positive

Examination topics

Contents of the Lecture

Reading list

Teil 1: Carl-Erik Särndal, Bengt Swensson, Jan Wretman: Model Assisted Survey Sampling. Springer Series in Statistics, 1992
Teil 2: S. Laaksonen: Survey Methodology and Missing Data: Tools and Techniques for Practitioners. Springer 2018
P. Christen: Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection (Data-Centric Systems and Applications), Springer
Teil 3, Teil 4: : C. P. Robert, G. Casella: Introducing Monte Carlo Methods with R. Springer Use R Series, 2010

Association in the course directory

Last modified: Mo 07.09.2020 15:20