230136 UE Specific Multivariate Methods of Analysis in the Social Sciences (2022S)
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
Covid19 Information zum Unibetrieb - aktuelle Bestimmungen:
https://www.univie.ac.at/ueber-uns/weitere-informationen/coronavirus/?pk_campaign=HomeDE&pk_kwd=Covid-InfolinkRahmenbedingungen für digitale Prüfungen (Soziologie) https://soziologie.univie.ac.at/info/digpruef/Allgemeiner Hinweis: Für die Teilnahme an Lehrveranstaltungen in digitaler Form sind eine - möglichst stabile - Internetverbindung und die technischen Möglichkeiten erforderlich, um an Online-Einheiten partizipieren zu können (Computer, Mikro, ggf. Webcam). Bei Lehrveranstaltungen aus dem Bereich quantitative Methoden kommen mitunter spezielle Programme (z.B. Stata, SPSS) hinzu, die über den zentralen Informatikdienst von Studierenden vergünstig bezogen werden können.
https://www.univie.ac.at/ueber-uns/weitere-informationen/coronavirus/?pk_campaign=HomeDE&pk_kwd=Covid-InfolinkRahmenbedingungen für digitale Prüfungen (Soziologie) https://soziologie.univie.ac.at/info/digpruef/Allgemeiner Hinweis: Für die Teilnahme an Lehrveranstaltungen in digitaler Form sind eine - möglichst stabile - Internetverbindung und die technischen Möglichkeiten erforderlich, um an Online-Einheiten partizipieren zu können (Computer, Mikro, ggf. Webcam). Bei Lehrveranstaltungen aus dem Bereich quantitative Methoden kommen mitunter spezielle Programme (z.B. Stata, SPSS) hinzu, die über den zentralen Informatikdienst von Studierenden vergünstig bezogen werden können.
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mi 02.02.2022 10:00 bis Mo 21.02.2022 10:00
- Abmeldung bis So 20.03.2022 23:59
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Samstag
12.03.
09:30 - 10:30
Digital
Freitag
27.05.
09:30 - 16:15
Digital
Freitag
03.06.
09:30 - 16:15
Digital
Freitag
10.06.
09:30 - 16:15
Digital
Freitag
17.06.
09:30 - 16:15
Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Students have to deliver individual assignments and perform a research paper presentation, showing the quantitative skills acquired (e.g., proper use of statistical concepts, use of data, analyze data correctly and interpret the results accordingly). The final grade is based on all the following tasks:
- Active participation (10%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (30%)Important Grading Information:
If not explicitly noted otherwise, all requirements mentioned in the grading scheme must be met.
If a required task is not fulfilled, this will be considered as a discontinuation of the course. In that case, the course will be graded as ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfill the task on the student's side (e.g. a longer illness).
In such a case, the student may be de-registered from the course without grading.
Whether this exception applies is decided by the lecturer.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 will be entered into the electronic exam record as ‘fraudulently obtained’.The plagiarism-detection service (Turnitin in Moodle) can be used in course of the grading: Details will be announced by the lecturer.
- Active participation (10%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (30%)Important Grading Information:
If not explicitly noted otherwise, all requirements mentioned in the grading scheme must be met.
If a required task is not fulfilled, this will be considered as a discontinuation of the course. In that case, the course will be graded as ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfill the task on the student's side (e.g. a longer illness).
In such a case, the student may be de-registered from the course without grading.
Whether this exception applies is decided by the lecturer.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 will be entered into the electronic exam record as ‘fraudulently obtained’.The plagiarism-detection service (Turnitin in Moodle) can be used in course of the grading: Details will be announced by the lecturer.
Mindestanforderungen und Beurteilungsmaßstab
Students have to deliver individual assignments and perform a research paper presentation, showing the quantitative skills acquired (e.g., proper use of statistical concepts, use of data, analyze data correctly and interpret the results accordingly). The final grade is based on all the following tasks:
- Active participation (10%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (30%)Tasks are graded with a scale from 1 (excellent) to 5 (fail). Students have to respect the deadlines agreed for each task. If the student does not perform in one of the tasks according to the deadline, the course is considered failed. To have an overall positive evaluation, students need a grade of at least 4 for each task. Attendance at the sessions is expected, if a student misses more than one session, the course is considered failed.
- Active participation (10%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (30%)Tasks are graded with a scale from 1 (excellent) to 5 (fail). Students have to respect the deadlines agreed for each task. If the student does not perform in one of the tasks according to the deadline, the course is considered failed. To have an overall positive evaluation, students need a grade of at least 4 for each task. Attendance at the sessions is expected, if a student misses more than one session, the course is considered failed.
Prüfungsstoff
Literatur
Statistical Methods for the Social Sciences (5th Edition), Agresti
Other material will be indicated during the course.
Other material will be indicated during the course.
Zuordnung im Vorlesungsverzeichnis
in 905: Ausschließlich für das Pflichtmodul MA M Methoden
Letzte Änderung: Do 11.05.2023 11:28
Main topics of the course:
- Multiple regression and correlation
- Analysis of variance
- Model building with multiple regression
- Logistic regression
The following free software will be used R and RStudio. The course will be held digitally (Zoom and Moodle). To participate in this course, it is necessary that a stable internet connection and a computer with webcam and microphone are available. The language of the course is English.