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Analysis of Societal Data (2024/2025: Semester 1 – Fall)
Course aim
..
Course content
The social sciences study the relations between attitudes, opinions and behaviors. This variety of topics often results in complex research questions. For example, one may be interested in finding the best predictors of smoking, political preference or happiness. Alternatively, the aim may be to reduce the information in a questionnaire with 200 questions into a limited number of variables.
This module is recommended for students with an interest in sociology, economics, geography, criminology, empirical political sciences, social psychology and focuses on logistic regression, a multiple regression model that can be used to predict dichotomous data such as yes/no decisions. Following the theoretical introduction, the student learns to apply these models on a real data set from an international survey using SPSS.
Schedule:
This course is taught during the last five weeks of the semester. It uses the same timeslot as the UCACCMET23 group did during the first ten weeks.
Registration:
During the UCACCMET23 course, students will be asked for their preferences in follow-up module and registered in the week before it starts.
Any student who still needs/wants a module without being registered for UCACCMET23 at that moment, can sign up through ucu.curriculum@uu.nl (cc tutor) at least one week before the start of the module. These other students will be lotteried into any remaining places, so also need to list a backup module.
Schedule:
This course is taught during the last five weeks of the semester. It uses the same timeslot as the UCACCMET23 group did during the first ten weeks.
Registration:
During the UCACCMET23 course, students will be asked for their preferences in follow-up module and registered in the week before it starts.
Any student who still needs/wants a module without being registered for UCACCMET23 at that moment, can sign up through ucu.curriculum@uu.nl (cc tutor) at least one week before the start of the module. These other students will be lotteried into any remaining places, so also need to list a backup module.
Instructional formats
UCU module
Examination
Exam
Required | Weight 100% | ECTS 2.5
Entry requirements and preknowledge
Entry Requirements
The following course module must be completed:
Preknowledge
This module follows directly after UCACCMET23
Languages
- English
Competences
-
Academic writing
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Research skills
-
Presenting
-
Collaboration
Course Iterations
Related studies
Exams
There is no timetable available of the exams
Required Materials
No information available on the required literature
Recommended Materials
No information available on the recommended literature
Remarks
This module follows directly after UCACCMET23
Coördinator
dr. K.T. Namesnik PhD | K.T.Namesnik@uu.nl |
Lecturers
dr. E.M. Grandfield PhD | e.m.grandfield@uu.nl |
Enrolment
Attention: this course is not open to students from other faculties, so subsidiary students can't enroll for this course.
Enrolments not in OSIRIS
Permanent link to course page
Show in the Course-Catalog