MSc students of Psychology, with the exception of students of the specialisation of Methodology and Statistics because of overlap with other courses
The following subjects are covered by the course:
- Univariate analysis: description of frequency distributions and measures of central tendency and variation;
- Bivariate analysis: estimating and testing relationships between two variables;
- Dimension reduction and scale construction: finding underlying dimensions for a set of items, and estimating reliability and validity for psychological scales;
- Regression and analysis-of-variance: predicting one variable by a set of other variables;
Most of the techniques will have been covered in Bachelor courses. What’s new is that in the set of course assignments students are consistently placed in the role of psychological researchers, and are asked to practice doing the following:
- Choosing the most appropriate statistical technique given the nature of the research question and the data;
- Applying the techniques with SPSS on real, “dirty” data, which implies a strong emphasis on trouble shooting: most notably, the student should be able to check and provide remedies for assumption violations and outliers;
Reporting the results in an appropriate way (both technically and psychologically), in accordance (at least globally) with APA-standards for text, tables, and figures.
The general objective of the course is to give students the knowledge of and practical skills in the most commonly used data analysis techniques that they might need for their masters thesis in psychology. The more specific goals are the following:
- Learning to understand the general principles, possibilities and complications, especially in regard to the assumptions of the techniques discussed in the course.
- Learning to choose the right technique for a research question and to perform the appropriate data analyses with SPSS.
- Learning to report the results of these data analyses following the APA rules for scientific writing in psychology.
Applied Data Analysis:
- Workgroups (1st semester)
- Exams (1st semester)
- Lectures (2nd semester)
- Workgroups (2nd semester)
- Exams (2nd semester)
Students need to enroll for lectures and work group sessions. Please consult the Instructions registration
If you have any question, please contact our exchange coordinator
Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date; students who are not registered will not be permitted to take the examination. Registering for exams
Mode of instruction
Eight lectures in which techniques are explained and illustrated in the applied way described above. Five work groups in which the course assignments are discussed.
Attendance of workgroup meetings is obligatory.
Examination and graded take home assignment.
The Faculty of Social 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
Information on blackboard.leidenuniv.nl
- Field, A. (2013). Discovering statistics using SPSS. Fourth Edition. London: Sage. ISBN (paperback): 9781446249185.
- Lecture notes.
Enrolment and registration for the examination
NB: This course is not intended for master students in Methodology and Statistics.
Students need to enrol for the course via uSis at the Master enrolment day that takes place at the start of each semester. They have to further register for each examination. Students are not allowed to sit an examination without being registered. It is possible to register up as from 6 weeks to 10 calendar days before the examination
Dr. P de Heus
Tel.: 071-527 3716