General Information
| Course Code | S_QNRM |
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| Credits | 6 EC |
| Period | P1 |
| Course Level | 200 |
| Language of Tuition | Dutch / English |
| Faculty | Fac. of Social Sciences and Humanities |
| Course Coordinator | dr. F.A. Nagel |
| Examiner | dr. F.A. Nagel |
| Teaching Staff |
L.S. Mastenbroek MSc dr. F.A. Nagel S.A. Khan |
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Part of programme(s)
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Practical Information
You need to register for this course yourself. The (de)registration deadlines can be found on VU.nl
| Teaching Methods | Computer lab, Study Group, Written partial exam, Lecture |
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Target audiences
This course is also available as:
Course Objective
Upon completion of this course, the student can:
- justify the choice of an appropriate observational or experimental research design based on causal models involving confounders, mediation, and moderation, as well as considerations regarding internal and external validity;
- construct a scale, perform reliability analysis and factor analysis in R, and interpret the results;
- apply linear regression analysis in R and interpret the results;
- apply analysis of variance in R and interpret the results.
Course Content
In this course, students learn the basics of multivariate statistical techniques commonly used in quantitative research in communication science. The emphasis is on testing hypotheses about cause-and-effect relationships and the interpretation of the analysis results, both in experimental and in non-experimental research. This knowledge is useful not only for properly testing hypotheses yourself, but also for critically evaluating research conducted by others.
The student learns the logic and purpose of experimental and observational research designs, as well as the advantages and disadvantages in terms of internal and external validity. Within the context of causal modelling, models with confounding variables, mediation and moderation will be discussed and results of analyses will be related to these causal models. Reliability analysis and factor analysis are applied in order to learn how to construct a reliable scale. Building upon the first year’s course Descriptive and Inferential Statistics, multivariate data analysis techniques will be introduced, focusing on analysis of variance and linear regression analysis. All mentioned techniques are applied using R.
Additional Information Teaching Methods
lectures, working groups and R labs
Method of Assessment
presentations, tentamen
Additional Information Target Audience
Second year students bachelor Communication ScienceAdditional Information
The language of instruction for this course is “bilingual”, which means that the lectures are held in English but the working groups are offered separately in English or Dutch. If you are following the English-language program, please sign up (if registration is possible) for the English-language working groups.