Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

040639 UK Exact Tests not only for Experimental Economics (MA) (2015W)

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

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. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 07.10. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 14.10. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 21.10. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 28.10. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 04.11. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 11.11. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 18.11. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 25.11. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 02.12. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 09.12. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 16.12. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 13.01. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 20.01. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 27.01. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock

Information

Aims, contents and method of the course

This course is about understanding what can go wrong big time when relying on asymptotic
theory and understanding which approaches do what they say they do. Exact testing refers
to methods do exactly this, they have properties that can be formally proven. Claims that
are not based on a handful of simulations when the underlying set of possible data
generating processes is so rich that one can never simulate many.

Assessment and permitted materials

The grade is made up of a) a midterm, b) a final and c) homeworks that involve finding
data sets, and analyzing data sets. Each of these three parts will be separately graded and
counts equally towards the final grade.
Prerequisites: knowledge of statistics at an undergraduate level.

Minimum requirements and assessment criteria

In this course we will give an overview and understand of existing and new methods for
testing hypotheses and running regressions that are exact. One goal of this course is to teach
students how to use R in order to analyze data sets. Laptops will be used in class to
demonstrate methods. Students will learn how to analyze data sets and how to read and
understand empirical papers.

Who is this course for? Anyone who is curious and
who is genuinely interested in uncovering what is hidden in the data and who is interested
in making mathematically sound claims. Of course many applications cannot be dealt (yet)
with an exact method as often there is too much going on. However this course will
demonstrate that there are lots of relevant areas where one can make exact statements,
including running linear regressions.

Examination topics

Statistics is a science about how to analyze data. Classical statistical methods often, in fact
most statistical methods typically make claims about data sets that are not in accordance
with the underlying theory and methodology. This is because they make claims about
significance that are based on assuming that the data is infinitely large (they are based on
asymptotic theory). Remember that typically we do not think that the data is normally
distributed, but that is approximately and we will talk about why this sort of approximation
is not what one needs.

Reading list

Association in the course directory

Last modified: Mo 07.09.2020 15:29