Analysis of Societal Data (2025/2026: periode 1)

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Cursusdoel

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Vakinhoudelijk

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.

Werkvormen

UCU module

Toetsing

Exam

Verplicht | Weging 100% | ECTS 2,5

Ingangseisen en voorkennis

Ingangseisen

Er moet voldaan zijn aan de cursus:

Voorkennis

This module follows directly after UCACCMET23

Voertalen

  • Engels

Competenties

  • Academisch schrijven
  • Onderzoeksvaardigheden
  • Presenteren
  • Samenwerken

Cursusmomenten

Gerelateerde studies

Tentamens

Er is geen tentamenrooster beschikbaar voor deze cursus

Verplicht materiaal

Er is geen informatie over de verplichte literatuur bekend


Aanbevolen materiaal

Er is geen informatie over de aanbevolen literatuur bekend

Opmerkingen

This module follows directly after UCACCMET23

Coördinator

dr. K.T. Namesnik PhD K.T.Namesnik@uu.nl

Docenten

dr. E.M. Grandfield PhD e.m.grandfield@uu.nl

Inschrijving

Let op: deze cursus is niet toegankelijk voor studenten van andere faculteiten, bijvakkers mogen zich dus niet inschrijven.

Inschrijving niet via OSIRIS
Permanente link naar de cursuspagina
Laat in de Cursus-Catalogus zien