Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.
040639 UK Exact Tests not only for Experimental Economics (MA) (2017S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mi 15.02.2017 09:00 bis Mi 22.02.2017 12:00
- Abmeldung bis Di 14.03.2017 23:59
Details
max. 50 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Donnerstag 02.03. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 09.03. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 16.03. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 23.03. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 30.03. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 06.04. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 27.04. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 04.05. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
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Donnerstag
11.05.
09:45 - 11:15
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Seminarraum 4 Oskar-Morgenstern-Platz 1 1.Stock - Donnerstag 11.05. 11:20 - 13:00 Seminarraum 4 Oskar-Morgenstern-Platz 1 1.Stock
- Donnerstag 18.05. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 01.06. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 08.06. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 22.06. 09:45 - 11:15 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Donnerstag 29.06. 09:45 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
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.
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.
Mindestanforderungen und Beurteilungsmaßstab
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.
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.
Prüfungsstoff
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.
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.
Literatur
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:29
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.