Prospectus

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Multivariate Data Analysis

Course
2022-2023

Students of the Dutch bachelor’s programme, see Multivariate data-analyse

Entry requirements

  • To be admitted to the Multivariate Data Analysis (MVDA) course, students must have successfully completed the Introduction to Methods and Statistics and Inferential Statistics courses.

  • The MVDA course forms an admission requirements for the third-year bachelors’ project.

Description

This course provides students with an overview of the standard models for the multivariate analysis of psychological research data. Different models are suitable for different types of data. Examples of such models include regression analysis and variance analysis, as well as more advanced versions of these models. Students learn how to answer a research question by using a model. In addition, they learn to work with relevant statistical software.

Course objectives

  • Knowledge and understanding of the key concepts and foundational principles of the standard models for multivariate data analysis;

  • Learning which analytical method to use to answer a particular type of research question; and

  • Acquiring skills in working with statistical software for multivariate data analysis.

Timetable

For the timetable of this course please refer to MyTimetable

Registration

Education

Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register up to 5 days prior to the start of the course. The exception here is that first-year bachelor students are assigned and registered for all components in the first semester or academic year by the administration of their bachelor programme. The programme will communicate to these students for which course components and for which period the registration applies.

Exams

It is mandatory for all students, including first-year bachelor students, to register for each exam and to confirm registration for each exam in My Studymap. This is possible up to and including 10 calendar days prior to the examination. You cannot take an exam without a valid pre-registration and confirmation in My Studymap.

Carefully read all information about the procedures and deadlines for registering for courses and exams.

Students who take this course as part of a LDE minor or a premaster programme, exchange students and external guest students will be informed by the education administration about the current registration procedure.

Mode of instruction

7 2-hour lectures, 7 1-hour computer practicals and 7 2-hour work group sessions. Recordings of the lectures are available as weblectures.

The lectures

Each course week begins with a lecture to introduce and explain course material. The lectures also cover additional and new topics that are included in the examination. As preparation for the lectures students are required to study the chapters assigned for that week. The lectures primarily focus on course objectives 1 and 2.

The computer practicals

The computer practicals and work group sessions take place on the day following the lectures. During the computer practicals students practise data analysis on the basis of exercises. Comparable assignments are also used in the SPSS-skills tests. The computer practicals primarily contribute to course objective 3. Attendance is compulsory for the computer practicals. A missed practical has to be compensated at a later time.

Information for retakers:
Students who retake the SPSS test also have to re-attend the SPSS practicals.

The workgroups

Besides the lectures, workgroup sessions are provided in which workgroup exercises will be discussed. Presence at these workgroups is not mandatory, but when students decide attend the workgroups, they are expected to make the specific workgroup assignments in advance. In addition, they are offered the opportunity to practice new exercises during the work group sessions. At the end of each week, a short elaboration of the exercises is published on Brightspace. The work group sessions contribute to course objectives 1, 2 and 3.

Assessment method

The assessment consists of two components:
1. A written examination consisting of 30 multiple-choice questions, each with 4 alternatives, covering both theory and statistical calculations from the literature, the work group sessions, and the lectures (Course objectives 1 and 2).
2. An SPSS skills test covering the various aspects of students’ skills in working with SPSS as well as in describing and interpreting statistical output (Course objective 3).

The final grade is a weighted average of the examination grade (60%) and the grade for the SPSS skills test (40%).
Important notice: students who did not fulfill the attendance requirements of the computer practicals will not be allowed to participate in the SPSS test.

The Institute of Psychology uses fixed rules for grade calculation and compulsory attendance. It also follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of these three policies.

Reading list

Texts in the MVDA Exercise book and additional articles on Brightspace. In addition to assignments for the practicals and workgroup sessions, this workbook also contains various texts, all of which are also part of the examination material. The workbook can be ordered from Readeronline.

Contact information