230136 UE Specific Multivariate Methods of Analysis in the Social Sciences (2023W)
Continuous assessment of course work
Labels
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 25.08.2023 10:00 to Tu 19.09.2023 10:00
- Registration is open from Fr 22.09.2023 10:00 to Tu 26.09.2023 10:00
- Deregistration possible until Fr 20.10.2023 23:59
Details
max. 22 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Friday
13.10.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Friday
20.10.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Friday
03.11.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Friday
17.11.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Friday
24.11.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Saturday
25.11.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
Friday
01.12.
09:45 - 13:15
Class Room 4 ZID UniCampus Hof 7 Eingang 7.1 2H-O1-33
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 (20%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (20%)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.
- Active participation (20%)
- Writing assignment I (30%)
- Writing assignment II (30%)
- Research papers presentation (20%)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.
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), Alan 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: We 20.09.2023 16:28
Main topics of the course:
- Multiple regression and correlation
- Model building with multiple regression
- Logistic regression
The following free software will be used: R and RStudio. The language of the course is English.