Universität Wien

040088 UE Empirical Methods I (MA) (2019W)

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

Pre-requisites:

Admission to the Master's programme

Attendance:

As part of the course grade, your class participation will be assessed every session. You will automatically fail the class if you miss more than 10% of sessions.
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: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 28.10. 08:00 - 11:15 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 04.11. 13:15 - 16:30 Hörsaal 15 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 11.11. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 18.11. 09:45 - 13:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 25.11. 08:00 - 11:15 Hörsaal 12 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 02.12. 08:00 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 09.12. 09:45 - 13:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 16.12. 09:45 - 11:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 13.01. 09:45 - 13:00 Hörsaal 16 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

This course is an introductory class on empirical methods and data analysis which precedes the follow-up class “Empirical Methods II”. The goal of this introductory course is for students to learn the fundamental techniques and obtain the basic skills required in empirical research. Our theoretical sessions will cover tools and stages required for running empirical projects (e.g. research design, measurement, methods of data collection) with a special focus on the pre-evaluation stage of an empirical work. Our applied sessions will introduce the students to basic programming skills, allowing them to prepare their data for 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 is also applied during a project where students actively develop the necessary steps for conducting their own empirical research projects.

Assessment and permitted materials

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 40%, the exam for 30% and class participation accounts for 30% of the final grade.

Minimum requirements and assessment criteria

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%]

Examination topics

Students are required to know and have understood all topics discussed in class and presented on the lecture slides.

Reading list

Necessary literature will be discussed in class.

Association in the course directory

Last modified: Mo 07.09.2020 15:19