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040081 UE Empirical Methods II (MA) (2020S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 10.02.2020 09:00 bis Mi 19.02.2020 12:00
- Anmeldung von Di 25.02.2020 09:00 bis Mi 26.02.2020 12:00
- Abmeldung bis Do 30.04.2020 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Mittwoch 04.03. 15:00 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
- Mittwoch 22.04. 11:30 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Freitag 24.04. 15:00 - 18:15 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Montag 27.04. 11:30 - 14:45 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Mittwoch 29.04. 15:00 - 18:15 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Donnerstag 30.04. 16:50 - 20:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Mittwoch 06.05. 16:45 - 18:15 Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock
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Mittwoch
20.05.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock - Mittwoch 20.05. 15:00 - 16:30 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Montag 25.05. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Mittwoch 27.05. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Donnerstag 04.06. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
- Donnerstag 04.06. 18:30 - 20:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
- Dienstag 30.06. 09:45 - 11:15 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
This course complements “Empirical Methods I” and builds on the knowledge acquired in that introductory class. The goal of this follow-up course is for students to learn how to work with data and analyse it against the backdrop of a given research question. After a brief recap of the contents of “Empirical Methods I”, we will delve into data analysis both in an applied and theoretical manner. Our theory sessions will mainly focus on descriptive and inference statistics for cross-sectional data. Our applied sessions will revisit the programming skills and theoretical know-how of students and introduce data analysis using statistical programming software. Students will participate by reading and presenting scientific articles in some of the highest ranked strategy journals. Knowledge gained in this course and its preceding class “Empirical Methods I” is also applied during a project where students actively conduct their own empirical research.
Art der Leistungskontrolle und erlaubte Hilfsmittel
Students will be assessed based on their class participation (class work, home assignments and a presentation of an empirical paper), a written exam and an empirical project (own paper and a presentation of own findings). The final project (including presentation) accounts for 35%, the exam for 35% and class participation accounts for 30% of the final grade.
Mindestanforderungen und Beurteilungsmaßstab
Please be aware that attendance during the first session of this course is absolutely mandatory. If students miss the first session without contacting the lecturer in writing (at the very latest until 24 hours before the first session), giving a relevant reason/proof (e.g. illness=doctor's certificate, exam=confirmation by the examiner) for their absence, they will be deregistered from the course and their place will automatically be awarded to the next in line on the waiting list. After that, students are allowed to miss 10% of the classes without any consequences (2.25 hours). Exceeding this threshold would result in failing the class. In order to pass the course, at least 50% of the total 100% are required. Please note that TURNITIN will be used in order to test all written coursework (e.g. the final project) for possible plagiarism.
Grading scheme: [0%;50%) [50%;62.5%) [62.5%;75%) [75%;87.5%) [87.5%;100%]
Grading scheme: [0%;50%) [50%;62.5%) [62.5%;75%) [75%;87.5%) [87.5%;100%]
Prüfungsstoff
Students are required to know and have understood all topics discussed in class and presented on the lecture slides.
Literatur
Jeffrey M. Wooldridge (2013) Introduction to Econometrics: EMEA Edition
Additional literature will be discussed in class.For further information, please refer to: https://strategy.univie.ac.at/
Additional literature will be discussed in class.For further information, please refer to: https://strategy.univie.ac.at/
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Fr 12.05.2023 00:12