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After completing this course students are able to:
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determine which statistical model should be used to investigate different types of research questions,
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execute the corresponding analyses using SPSS, interpret the results, and write a consequent report.
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The content of this course overlaps with UCACCMET22/UCACCSTA21. Do not take both.
The subjects investigated by social scientists are rather complex; as a result, it is usually necessary to use many (‘multi’) variables to be able to give an adequate description of a subject. In the Multivariate statistical analysis techniques course, the theory and application of multivariate statistical models is discussed in depth. The techniques that are dealt with include multiple regression analysis, logistic regression, AN(C)OVA, MAN(C)OVA, and repeated measures analysis. These models can be used to investigate the relations among many variables simultaneously, and thus provide an accurate description of the subject of interest.
Format
For a period of 10 weeks, students and teachers meet twice a week for two hours. During the first meeting, the teachers introduce the topic of the week. Before the second meeting, the students have to execute (using SPSS) statistical analyses related to the topic of the week and write a report on the results. During the second meeting, two of the students give a short presentation of the results obtained (after 10 weeks each student has given a presentation). These presentations lead to a discussion of the exercises by all students and teachers.
Directly following this 5 ECTS Multivariate statistical analysis course, students continue in one of the four separate 5 week course modules (2,5 ECTS). Separate outlines are available for these course modules. The topics of these course modules are:
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UCACCMET2A: Analysis of Behavioral data
This module is recommended for students with an interest in different areas of psychology and cognitive sciences and focuses mainly on factor analysis techniques
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UCACCMET2B: Analysis of Societal data
This module is recommended for students with an interest in sociology, economics, geography, criminology, empirical political sciences, social psychology and focuses mainly on logistic regression analysis.
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UCACCMET2C: Analysis of Econometric data This module focuses on the analysis of cross-sectional data and time series based on economic data. However, trend analysis is used in many other fields of research, i.e. climate change, evolution, age/generation related research. This module is recommended for students with an interest in economics, especially econometrics, but may be interesting for students in many other fields.
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UCACCMET2D: Qualitative research techniques
This module is recommended for students with an interest in non-quantitative data, as often used in for instance anthropology.
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