230136 UE Specific Multivariate Methods of Analysis in the Social Sciences (2022S)
Continuous assessment of course work
Labels
REMOTE
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.
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 We 02.02.2022 10:00 to Mo 21.02.2022 10:00
- Deregistration possible until Su 20.03.2022 23:59
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Saturday
12.03.
09:30 - 10:30
Digital
Friday
27.05.
09:30 - 16:15
Digital
Friday
03.06.
09:30 - 16:15
Digital
Friday
10.06.
09:30 - 16:15
Digital
Friday
17.06.
09:30 - 16:15
Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
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.
Minimum requirements and assessment criteria
Task 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.
Examination topics
Reading list
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.
Association in the course directory
in 905: Ausschließlich für das Pflichtmodul MA M Methoden
Last modified: Th 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.