Multivariate Data Analysis for Social Sciences

6 ECTS credits
180 h study time

Offer 2 with catalog number 1015169BNR for all students in the 1st semester at a (B) Bachelor - advanced level.

Semester

1st semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Yes

Enrollment Requirements

Je hebt 'Statistiek II voor de sociale wetenschappen' gevolgd, alvorens dit opleidingsonderdeel op te nemen.

Taught in

Dutch

Faculty

Faculty of Social Sciences & SolvayBusinessSchool

Department

Sociology

Educational team

Hadewijch Vandenheede (course titular)
Juliette De Vestel
Tom De Winter

Activities and contact hours

39 contact hours Lecture
32 contact hours Seminar, Exercises or Practicals
157 contact hours Independent or External Form of Study

Course Content

This course consists of four parts:

Introduction
Part 1 deals with translating problem definitions into analyses. In addition, the relevant basic principles of both descriptive and inferential statistics are recapitulated, and different types of multivariate analysis techniques are outlined.
Dependence techniques
Part 2 addresses the following topics: multiple regression analysis and generalized linear models, model specification in regression, and logistic regression analysis.
Independence techniques
Part 3 probes into principal components analysis and factor analysis, amongst other techniques.
Data analytic excercises
Part 4 is an application of the techniques taught on a specific research question.

This course looks into data analysis techniques from both a theoretical/conceptual and a practical point of view. In the seminars, focus is on theory; in the practicals, focus is on conducting statistical analyses in SPSS and on the correct interpretation of statistical outputs.

Course material

Digital course material (Required) : Slides van hoor- en werkcolleges en extra infomateriaal, H. Vandenheede & T. De Winter, 2017
Handbook (Required) : Inleiding multivariate analyse, Voor de sociale wetenschappen, K. Neels, Acco, 9789462922518, 2017

Additional info

This subject is taught in Dutch.

The exercise manual, the manual "Inleiding multivariate analyse voor de sociale wetenschappen”, the slides of the lectures and practicals constitute the core course material.

For more information: see study guide.

Learning Outcomes

General Competences

Specific objectives are specified at the beginning of each class. Summed up: at the end of this course, students should be able:

to explain in their own words the basic principles of multivariate data analysis;
to elaborate upon the theoretical background of the statistical methods;
to make a well-founded choice for a certain analysis technique taking the research question into account;
to perform the data manipulation techniques taught in class (in SPSS);
to use SPSS to perform the data analyses taught in class, to critically interpret their results and to report them correctly and ethically.

Grading

The final grade is composed based on the following categories:
Written Exam determines 60% of the final mark.
Practical Exam determines 20% of the final mark.
Other Exam determines 20% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

Written Exam with a relative weight of 60 which comprises 60% of the final mark.

Within the Practical Exam category, the following assignments need to be completed:

SPSS Exam with a relative weight of 20 which comprises 20% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

Data exercises with a relative weight of 20 which comprises 20% of the final mark.

Additional info regarding evaluation

First session:

Written exam: 20% of marks is on a practical SPSS exam, 60% of marks is on a written exam covering both theory and exercises, 20 % is on a data application
Students need to pass all exam sections (SPSS exam, written exam, data application) in order to obtain a credit for this course
Non-attendance on one of the exam sections implies a ‘non-attendance’ as final result
The exam sections ’SPSS exam’, ‘written exam’ and 'data application' are weighted for 20%, 60% and 20% respectively; yet only when you pass each section. In case of not passing every section, the lowest grade counts as the final mark
The specific results of the different exam sections (SPSS exam, written exam, data application), will be transferred to second session, in case of obtaining at least 50% on the exam section concerned

Second session:

Idem first session.
Students need to pass all exam sections (SPSS exam, written exam, data application) in order to obtain a credit for this course
In case of not obtaining a credit for this course, results of specific exam sections are not transferable to the next academic year

For more information: see study guide.

Allowed unsatisfactory mark

The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context