Universität Wien
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230072 UE B10 Multivariate Methods - Exercise (2025W)

4.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Prüfungsimmanente Lehrveranstaltung

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

    Termine (iCal) - nächster Termin ist mit N markiert

    • Montag 13.10. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 20.10. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 27.10. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 03.11. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 10.11. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 17.11. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 24.11. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 01.12. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 15.12. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 12.01. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 19.01. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)
    • Montag 26.01. 15:00 - 16:30 PC-Raum 1 UniCampus Hof 7 Eingang 7.1, 1.OG ( 2H-O1-13)

    Information

    Ziele, Inhalte und Methode der Lehrveranstaltung

    This course offers a practical introduction to the application of multivariate statistical analysis methods. The focus is on independently conducting regression analyses to answer social science questions using the statistical program STATA. The course combines theoretical fundamentals with practical exercises. Various aspects of regression analysis are covered, including the implementation and interpretation of simple and multiple regressions. A brief introduction to STATA is part of the course.

    Art der Leistungskontrolle und erlaubte Hilfsmittel

    The exercise is designed as a series of topic blocks.
    For each topic, relevant data sets and syntax templates (DO files) are provided.
    After each block, students will have to work on homework assignments to earn partial achievements.
    A total of six partial achievements must be completed.

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    Important Grading Information:
    All students who received a place in the course are assessed if they have not deregistered from the course in due time or if they have not credibly shown an important reason for their failure to deregister after the cause for this reason does no longer apply
    Students who credibly show an important reason (e.g. a longer illness) for the withdrawal from a course with continuous assessment are not assessed.
    Whether this exception applies is decided by the lecturer. The request for deregistration must be submitted immediately.
    For a positive assessment of the course, all partial achievements must be fulfilled.
    The plagiarism-detection service (Turnitin in Moodle) can be used in course of the grading.
    The use of AI tools (e.g. ChatGPT) for the production of texts is only permitted if this is expressly requested by the lecturer (e.g. for individual work tasks).
    In order to ensure good scientific practice, the lecturer can provide for a "grading-related discussion" of the written work submitted, which must be completed successfully.
    If any requirement of the course has been fulfilled by fraudulent means, be it for example by cheating at an exam, plagiarizing parts of a written assignment or by faking signatures on an attendance sheet, the student's participation in the course will be discontinued, the entire course will be graded as "not assessed" and recorded accordingly.
    You can find these and other provisions in the study law: https://satzung.univie.ac.at/studienrecht/.
    In case you have received three negative assessments of a continuously assessed course and want to register for a fourth attempt, please make sure to contact the StudiesServiceUnit Sociology during the registration period (for more information see "third attempt for continuously assessed courses" https://soziologie.univie.ac.at/info/pruefungen/#c56313)

    Mindestanforderungen und Beurteilungsmaßstab

    Students deepen their knowledge of the methods learned through homework assignments as partial achievements.
    A total of 6 partial assignments must be completed. The points earned in each homework assignment are equally weighted in the final grade. A minimum of 30 out of 60 points is required to pass the course.
    All partial assignments must be completed on time and receive a passing grade. Attendance is mandatory; students may miss a maximum of 2 sessions.

    Prüfungsstoff

    Literatur

    Kohler, Ulrich & Kreuter, Frauke (2012): Data analysis using Stata. Stata Press. (Multiple editions)

    Additional resources will be shared during the course.

    Zuordnung im Vorlesungsverzeichnis

    Letzte Änderung: Sa 28.06.2025 17:06