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Multivariate Analysis: from Data to Report


This course is taught in Dutch in the academic year 2019-2020

Admission requirements

Only students enrolled as Bachelor’s students for CA-OS may participate in this course.

To participate in this course, students must pass the following courses from the propaedeutic course CA-OS:

  • "Social scientific research in practice",

  • "Culture deciphered: statistics in practice",

  • "Scientific writing and academic (re) presentation" (AV1)

  • "Research practice" (AV2)

  • "The academic debate" (AV3).

Language of Instruction

Lectures are taught in Dutch.
Examination (assignments and written exam) will be held in Dutch.


This course is an introduction to the processing of multivariate data, in particular nominal and / or ordinal data. It includes exercises in analysing files using the SPSS modules for Multiple Categorical Analysis (MCA) and Categorical Principal Components Analysis (CATPCA).

In this course we also work on the analysis of data collected by students themselves during Fieldwork NL.

The assessment consists of two parts; an open book examination including multiple choice and open questions, and a multivariate analysis paper on the fieldwork data. Students should therefore be involved from the beginning in the analysis of their own fieldwork data. Students should bring with them their research proposal and their final questionnaire immediately before the first meeting, at which they are expected to work on a codebook for the analysis of the data.

Course Objectives

  1. To offer insight into methods and techniques for multivariate analysis. In particular to be able to explain what multivariate analysis is for and to explain, for a given research question and collected data provided, which of the techniques treated is or are potentially suitable to use to analyse the data. Special attention is given to the importance of distinguishing among MCA, CATPCA, factor analysis and multiple regression.

  2. To offer experience in multivariate analysis, for example by using one or more techniques when analysing data. Students should note that they will not be expected immediately on completing the course to demonstrate abilities similar to those of experienced researchers, for that takes a number of years. The aim is rather to ensure that students will have completed the analysis process at least once.


  • The lecture schedule can be found on the website

  • Practicals take place on t.b.a.. Classification per practical group is made in the first lecture - registration for these groups via Usis is not necessary.

Mode of instruction

Total 5 ECTS = 140 study tax hours (sbu)

  • lecture 14 × 3 hours = 42 hours = 63 sbu

  • practical: 7 × 2 hours = 14 hours = 14 sbu (attendance required)

  • literature (articles + syllabus with assignments) ca. 378 pp = 63 sbu

Assessment method

  • Written examination (open book examination with both multiple-choice and open questions) about lecture material and assignments. The examination accounts for 80% of the final mark.

  • Compulsory participation in practicals. Attendance at practicals will be checked.

  • Written analysis report (take-home assignment) on a multidimensional analysis of (BLO) data; accounts for 20% of the final mark.

Three assignments with deadlines during the course. These assignments will be assessed as sufficient or insufficient. These assignments are mandatory parts of the written analysis report you have to hand in at the end of the course. This means that the report will only be assessed and counted with the final grade of the course when all assignments are assessed as sufficient. If one or more of the assignments are assessed as insufficient, you will get a resit opportunity in the form of a replacement assignment at the end of the course. The size of this resit assignment depends on how many of your assignments are assessed as insufficient. You may miss 1 assignment, but only with a good reason and with the approval of the Examination Board. In this case too, the assignment must be retaken at the end of the course.

Note: both the examination and the paper must be passed.

Only the final mark will be registered in Usis and tests may be re-taken if results are inadequate (grade 5 or lower).

Registering exam

You are required to register in uSis for every exam. This can be done up to 10 calendar days prior to the examination. Read more


  • Registration takes place via Usis for the lectures and all (partial) examinations and possibly the resit. On the website on course registration you will find the registration periods and further information about the procedure.

  • For the Practicum registration in Usis not required: you will be assigned and informed in the first lecture.

  • In addition to registration in Usis registration on Blackboard is also required.


The detailed program of the course will be available on Blackboard. Participants must register for Blackboard on this course.


  • Field, Andy (2018). Discovering Statistics using SPSS. fifth edition

  • College sheet, made available via BlackBoard.

  • Articles available online; for titles and links see Blackboard

  • Chapters (reference, examples, available online) from SPSS Categories 17 manual:
    H. 1: Introduction;
    H. 3: CATPCA;
    H. 6: MCA;
    H. 10: CATPCA Examples;
    H. 13: MCA Examples.

  • The literature on the course Statistics / SPSS and M & T 2: Research techniques is assumed to be known.


Dr. Igor Boog