210017 UE BAK4.2: Quantitative Methods of Empirical Social Research (engl.) (2018W)
(engl.)
Prüfungsimmanente Lehrveranstaltung
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Eine Anmeldung über u:space innerhalb der Anmeldephase ist erforderlich! Eine nachträgliche Anmeldung ist NICHT möglich.
Studierende, die der ersten Einheit unentschuldigt fern bleiben, verlieren ihren Platz in der Lehrveranstaltung.Beachten Sie die Standards guter wissenschaftlicher Praxis.Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis). Ab WS 2018 kommt die Plagiatssoftware (‘Turnitin') bei prüfungsimmanenten Lehrveranstaltungen zum Einsatz.
Studierende, die der ersten Einheit unentschuldigt fern bleiben, verlieren ihren Platz in der Lehrveranstaltung.Beachten Sie die Standards guter wissenschaftlicher Praxis.Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis). Ab WS 2018 kommt die Plagiatssoftware (‘Turnitin') bei prüfungsimmanenten Lehrveranstaltungen zum Einsatz.
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 03.09.2018 08:00 bis Mo 17.09.2018 08:00
- Anmeldung von Do 20.09.2018 08:00 bis Mi 26.09.2018 08:00
- Abmeldung bis So 14.10.2018 23:59
Details
max. 35 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
No class on Wednesday 30 January. The last class will be on 23 January.
- Mittwoch 10.10. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 17.10. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 24.10. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 31.10. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 07.11. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 14.11. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 21.11. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 28.11. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 05.12. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 12.12. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 09.01. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 16.01. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 23.01. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
- Mittwoch 30.01. 13:30 - 14:45 Class Room 3 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-25
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
The final assessment will be based on the following components:
(1) Regular attendance in class (maximum 2 classes can be missed)
(2) 3 short homework assignments (30% of final grade). The assignments will be posted on Moodle at the end of the class, and have to be completed before the beginning of the following class. Joint homework is possible for maximum 2 students.
(3) 1 short test in December (20% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata outputs. Duration: max 45 minutes.
(4) Final assignment (50% of final grade). At the end of the course, the students will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. Final assignments need to be handed in by 31 March 2019.Please note that all four components are essential for the final grade, i.e. students have to be present in class, hand in 3 homework assignments, complete the short test in December, and hand in the final assignment.In cases of suspected plagiarism, students may be called upon to reasonably demonstrate that any work they have submitted is their own.
(1) Regular attendance in class (maximum 2 classes can be missed)
(2) 3 short homework assignments (30% of final grade). The assignments will be posted on Moodle at the end of the class, and have to be completed before the beginning of the following class. Joint homework is possible for maximum 2 students.
(3) 1 short test in December (20% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata outputs. Duration: max 45 minutes.
(4) Final assignment (50% of final grade). At the end of the course, the students will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. Final assignments need to be handed in by 31 March 2019.Please note that all four components are essential for the final grade, i.e. students have to be present in class, hand in 3 homework assignments, complete the short test in December, and hand in the final assignment.In cases of suspected plagiarism, students may be called upon to reasonably demonstrate that any work they have submitted is their own.
Mindestanforderungen und Beurteilungsmaßstab
The final assessment will be based on the following components:
(1) Regular attendance in class (maximum 2 classes can be missed)
(2) 3 short homework assignments (30% of final grade). The assignments will be posted on Moodle at the end of the class, and have to be completed before the beginning of the following class. Joint homework is possible for maximum 2 students.
(3) 1 short test in December (20% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata outputs. Duration: max 45 minutes.
(4) Final assignment (50% of final grade). At the end of the course, the students will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. Final assignments need to be handed in by 31 March 2019.Please note that all four components are essential for the final grade, i.e. students have to be present in class, hand in 3 homework assignments, complete the short test in December, and hand in the final assignment.In cases of suspected plagiarism, students may be called upon to reasonably demonstrate that any work they have submitted is their own.
(1) Regular attendance in class (maximum 2 classes can be missed)
(2) 3 short homework assignments (30% of final grade). The assignments will be posted on Moodle at the end of the class, and have to be completed before the beginning of the following class. Joint homework is possible for maximum 2 students.
(3) 1 short test in December (20% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata outputs. Duration: max 45 minutes.
(4) Final assignment (50% of final grade). At the end of the course, the students will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. Final assignments need to be handed in by 31 March 2019.Please note that all four components are essential for the final grade, i.e. students have to be present in class, hand in 3 homework assignments, complete the short test in December, and hand in the final assignment.In cases of suspected plagiarism, students may be called upon to reasonably demonstrate that any work they have submitted is their own.
Prüfungsstoff
In addition to the homework assignments and the short test in December, the students have to hand in a final assignment by 31 March 2019. The final assignment will focus on different topics covered in class, and will include basic data analysis using the Stata commands learnt in class. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course.
Literatur
Reading materials will be made available in the entrance hall of the Department of Government (Rathaustrasse 19/9) after the first class. Please regularly check the course page on Moodle for the updated reading list, and for additional reading materials.Suggested readings:
- Paul M. Kellstedt, and Guy D. Whitten. 2013. The fundamentals of political science research. Cambridge: Cambridge University Press
- Alan Agresti and Barbara Finaly. 2009. Statistical methods for the social sciences (fourth edition). New Jersey: Pearson Education International
- Alan C. Acock. 2014. A Gentle Introduction to Stata (4th Edition). College Station, Texas: Stata Press
- Paul M. Kellstedt, and Guy D. Whitten. 2013. The fundamentals of political science research. Cambridge: Cambridge University Press
- Alan Agresti and Barbara Finaly. 2009. Statistical methods for the social sciences (fourth edition). New Jersey: Pearson Education International
- Alan C. Acock. 2014. A Gentle Introduction to Stata (4th Edition). College Station, Texas: Stata Press
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:38
a) Principles and methods of quantitative empirical social research.
- What are the key features of empirical research based on quantitative methods?
b) Overview of basic statistics and their application.
- How can I describe and recode the collected "data"?
c) Learning basic commands of the statistical software Stata.
- How can I process my data efficiently?
d) Learning how to use Stata to analyze data and test hypotheses that are relevant in the social science.
- How can I test my hypotheses given the available data?