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230184 SE Multiple Linear Regression (2009W)
Continuous assessment of course work
Labels
Erster Termin: Mo 23.11.09 09:00-14:00 Teilnahme unbedingt erforderlich,
Sa 5.12.09, 13:00-18:00
Do 17.12.09, 10:00-15:00
Mo 11.01.10, 09:00-14:00
Letzter Termin: Mo 18.01.10, 09:00-14:00
Neues Institutgebäude (NIG), Universität Wien, Universitätsstraße 7, 1010 Wien
Kursraum A (23.11., 11.01., 18.01.) und Kursraum B (05.12., 17.12).ANMELDUNG: über univis ab sofort bis 16.11.2009, 12:00 Uhr
Sa 5.12.09, 13:00-18:00
Do 17.12.09, 10:00-15:00
Mo 11.01.10, 09:00-14:00
Letzter Termin: Mo 18.01.10, 09:00-14:00
Neues Institutgebäude (NIG), Universität Wien, Universitätsstraße 7, 1010 Wien
Kursraum A (23.11., 11.01., 18.01.) und Kursraum B (05.12., 17.12).ANMELDUNG: über univis ab sofort bis 16.11.2009, 12:00 Uhr
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).
- Registration is open from Fr 23.10.2009 13:05 to Mo 16.11.2009 12:00
- Deregistration possible until Mo 16.11.2009 12:00
Details
max. 35 participants
Language: German
Lecturers
Classes
Currently no class schedule is known.
Information
Aims, contents and method of the course
Assessment and permitted materials
- Participation required in all five classes
- 10-15 page problem-set paper on main concepts and interpretation of results, assigned after the last class OR 10-15 page paper on main concepts, challenges and interpretation of results based on the perceived topic of the Masters' thesis (50%). Deadline: 15 March 2010
- Homework and problem sets after each class, to be submitted at four set dates (40%)
- Continuous assessment of class participation (10%)
- 10-15 page problem-set paper on main concepts and interpretation of results, assigned after the last class OR 10-15 page paper on main concepts, challenges and interpretation of results based on the perceived topic of the Masters' thesis (50%). Deadline: 15 March 2010
- Homework and problem sets after each class, to be submitted at four set dates (40%)
- Continuous assessment of class participation (10%)
Minimum requirements and assessment criteria
Teilnahmevoraussetzungen: MA-Level.
Das Seminar ist für MA-Studierende konzipiert. Es findet im neu konzipierten MA-Modul der Fakultät für Sozialwissenschaften statt und kann als Zusatzmethodenveranstaltung besucht werden. Es ersetzt nicht die Pflichtmethodenveranstaltung der jeweiligen Studienrichtung.
Das Seminar ist für MA-Studierende konzipiert. Es findet im neu konzipierten MA-Modul der Fakultät für Sozialwissenschaften statt und kann als Zusatzmethodenveranstaltung besucht werden. Es ersetzt nicht die Pflichtmethodenveranstaltung der jeweiligen Studienrichtung.
Examination topics
Reading list
Dougherty, Christopher (2007) Introduction to Econometrics, 3rd edition, Oxford University Press.
Field, Andy (2009) Discovering Statistics using SPSS, 3rd edition, Sage Publications.
Agresti, Alan and Barbara Finlay (2008) Statistical Methods for the Social Sciences, 4th edition, Pearson Education.
Wooldridge, Jeffrey (2009) Introductory Econometrics, 3rd edition, South Western College.Additional literature references will be provided throughout the course.
Field, Andy (2009) Discovering Statistics using SPSS, 3rd edition, Sage Publications.
Agresti, Alan and Barbara Finlay (2008) Statistical Methods for the Social Sciences, 4th edition, Pearson Education.
Wooldridge, Jeffrey (2009) Introductory Econometrics, 3rd edition, South Western College.Additional literature references will be provided throughout the course.
Association in the course directory
in 905: MA Methoden oder MA EM Erweiterung Methoden |
in 121: Methoden, 3. Studienabschnitt
in 121: Methoden, 3. Studienabschnitt
Last modified: Mo 07.09.2020 15:39
Session 1: Review of basic statistical concepts; correlation between two variables
Session 2: Simple linear regression; the assumptions of OLS regression
Session 3: Multiple linear regression; interpretation and inference
Session 4: Types of explanatory variables: nominal independent variables; non-linearity; interaction effects; transforming independent variables
Session 5: Regression diagnostics and principles of model-building