For students of the Dutch bachelor’s programme in Psychology, see Experimenteel en Correlationeel onderzoek
This course follows on from the Introduction to Research Methods and Statistics course and Inferential Statistics, and presupposes the knowledge and skills taught there.
The course discusses basic methods used to analyse data from correlational and (quasi-)experimental research: (multiple) regression-analysis and analysis of variance.
To obtain knowledge and understanding of the principles and procedures of regression analysis and analysis of variance, and the statistical techniques used in the analysis of (quasi) experimental research.
To select, carry out, assess and report on the correct analysis in a given situation.
To gain skills in working with statistical software concerning regression analysis and analysis of variance.
Note: A complete list of course objectives is available on Blackboard.
For the timetables of your lectures, workgroups, and exams, select your study programme.
The Student Services Centre enrolls first-year students in lectures and work groups. However, students must register themselves in exams.
After the first year, students must register themselves in the first year course component they need to repeat: lectures, work groups and exams. A second (or higher) year student who needs only to repeat the SPSS skills test is required to attend the four SPSS work group meetings again. As such, he/she must also register again for these SPSS work groups. Enrolling for workgroups
Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the exam date; students who are not registered will not be permitted to take the examination. Registering for exams
Mode of instruction
The Experimental and Correlational Research course is taught over 8 successive weeks. It consists of weekly lectures and work group sessions in which we work with or without a computer. At the end of the week additional work group sessions are offered, which also involve working with or without a computer.
Each week the course starts with a lecture to introduce and explain the week’s course materials. The lecture is recorded and available as weblecture. Some extensions and new materials are also discussed during the lecture. The materials given in the lecture also form part of the examination materials. As preparation for the lectures students are required to study the chapters assigned for that week in the syllabus. The focus of the lectures is to gain knowledge and understanding of the principles and procedures of regression analysis and analysis of variance (course objective 1).
On one of the days following the lecture, there is a mandatory work group session. In the work group sessions the focus lies on obtaining knowledge and understanding of the principles and procedures of regression analysis and analysis of variance (course objective 1). In addition, students practise selecting, carrying out, assessing and reporting on the adequate analysis in a certain situation (course objective 2), as well as obtaining skills in working with statistical software concerning regression analysis and analysis of variance (course objective 3). Active participation in the work group sessions is mandatory.
In the additional work group sessions at the end of the week students are offered the opportunity to get some additional practice in statistical calculations, by hand or using SPSS. All students who would benefit from this extra support are free to attend these sessions.
The assessment consists of two components:
A written examination consisting of 40 multiple-choice questions, each with 4 alternatives, covering both theory and statistical calculations from the literature, the work group sessions, and the lectures.
An SPSS skills test covering the various aspects of the skills required to work with SPSS as well as to read the analysis output.
The final grade will be a weighted average of the examination grade (0.7) and the grade for the SPSS skills test (0.3).
The Faculty of Social and Behavioural Sciences has instituted that instructors use a software programme for the systematic detection of plagiarism in students’ written work. In case of fraud disciplinary actions will be taken. Please see the information concerning fraud.
Howell, D.C. (2014). Statistical Methods for Psychology (Leiden edition). Wadsworth: Cengage Learning.
Pallant, J. (2016). SPSS Survival Manual. Berkshire: McGraw-Hill.
IBM SPSS Statistics for Windows, Version 23*. Released 1012. Armonk, NY: IBM Corp., [www.surfspot.nl].
Additional materials provided on BlackBoard (lecture slides, assignments, workbook, etc.)
Drs. C.J. Verduin firstname.lastname@example.org