Entry requirements
This course follows on from the courses Introduction to Methodology and Statistics course and Inferential Statistics, and presupposes the knowledge and skills taught there.
Description
The course discusses basic methods used to analyse data from correlational and (quasi-)experimental research: (multiple) regression-analysis and analysis of variance.
Course objectives
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 Brightspace.
Timetable
For the timetable of this course please refer to MyTimetable
Registration
NOTE As of the academic year 2021-2022, you must register for all courses in uSis. You do this twice a year: once for the courses you want to take in semester 1 and once for the courses you want to take in semester 2.
Registration for courses in the first semester is possible from July. Registration for courses in the first semester is possible from December.
The exact date on which the registration starts will be published on the website of the Student Service Center (SSC). First year Bachelor students as well as premaster students will be registered by the Student Service Center; they do not need to register themselves.
The registration period for all courses closes five calendar days before the start of the course.
Also read the complete registration procedure
Mode of instruction
8 2-hour lectures and 8 2-hour mandatory tutorial sessions.
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 lectures can be attended in a lecture hall and via a live stream. The lectures will be made available as Weblectures.
The tutorials
The day after the lecture there is a tutorial session. In preparation for these sessions students have to complete a number of mandatory homework assignments, that will be checked by the teacher at the start. These sessions focus on applying the acquired knowledge in practice. Students also learn to work with IBM SPSS Statistics, a software package for statistical data analysis. The material covered in these work group sessions is also included in the examination. Students are required to bring the exercise book to every session. Attendance is mandatory. The tutorials focus on course objectives 1, 2, and 3.
Assessment method
The assessment consists of two components:
1. A written examination consisting of multiple-choice questions, 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 (70%) and the grade for the SPSS skills test (30%).
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
Howell, D.C. (2016). Statistical Methods for Psychology (Leiden edition). Wadsworth: Cengage Learning. ISBN 978-1-4737-2028-2
Pallant, J. (2020). SPSS Survival Manual (7th edition). Berkshire: McGraw-Hill. (Ch. 1-8 and 11) ISBN 978-0-03352-4949-7
IBM SPSS Statistics for Windows (versie volgt). Armonk, NY: IBM Corp., [www.surfspot.nl]
Exercise book Experimental and Correlational Research.
Additional materials provided on Brightspace (lecture slides, assignments, workbook, etc.).
Howell, D.C. (2014/2021). Statistical Methods for Psychology (Leiden edition). Wadsworth: Cengage Learning. ISBN 978-1-4737-8791-9
Pallant, J. (2020). SPSS Survival Manual (7th edition). Berkshire: McGraw-Hill. ISBN 978-0-03352-4949-7
IBM SPSS Statistics for Windows (versie 27). Armonk, NY: IBM Corp. Software for sale via www.surfspot.nl
Exercise book Experimental and Correlational Research 2021-2022.
Lecture slides (provided on Brightspace).
Contact information
Drs. Hemmo Smit
hsmit@fsw.leidenuniv.nl
Drs. Kees Verduin (SPSS)
verduin@fsw.leidenuniv.nl