Students of the Dutch bachelor’s programme, see Experimenteel en Correlationeel Onderzoek
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: correlation, simple and multiple regression analysis, one-way analysis of variance (ANOVA), planned comparisons, post hoc tests, and factorial ANOVA.
Course objectives
At the end of this course the student is able to:
understand the terms, principles, and procedures of correlation, regression analysis and analysis of variance
select a suitable statistical analysis based on the research question
calculate and test correlations, and to interpret and report the results
carry out simple and multiple regression analysis and to interpret and report the results
carry out one-way and two-way analysis of variance and to interpret and report the results
use the statistical software R for correlation analysis, regression analysis, and analysis of variance
Timetable
For the timetable of this course please refer to MyTimetable
Registration
Education
First-year bachelor students are assigned and registered for all components in the first 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. All other students (excl. minor and exchange) 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.
Exams
You must register for each exam in My Studymap at least 10 days before the exam date. Don’t forget! For more information, see the enrolment procedure.
You cannot take an exam without a valid registration 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 and 7 2-hour tutorial sessions.
Attendance at the tutorial sessions is mandatory. See Brightspace for more information.
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 can be attended in a lecture hall. The recordings of the lectures will be made available as Weblectures.
The tutorials
The tutorial sessions take place in the days after the lecture. In preparation for these sessions students have to complete a number of mandatory homework assignments. These sessions focus on applying the acquired knowledge from the literature and the lecture in practice. Students also learn to work with R, a software package for statistical data analysis. The material covered in these tutorial sessions is also included in the examination. Students are required to bring the exercise book to every session.
Assessment method
The assessment consists of two components:
1. A written examination covering both theory and statistical calculations from the literature, the work group sessions, and the lectures
2. An R skills test covering the various aspects of students’ skills in working with R as well as in interpreting and reporting the output.
The final grade is a weighted average of the examination grade (70%) and the grade for the R skills test (30%).
The Institute of Psychology uses fixed rules for grade calculation. 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. All students are required to take and pass the Scientific Integrity Test with a score of 100% in order to learn about the practice of integrity in scientific writing. Students are given access to the quiz via a module on Brightspace. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of these two policies.
Reading list
Howell, D.C. (2014/2021). Statistical Methods for Psychology (Leiden edition). Wadsworth: Cengage Learning. ISBN 978-1-4737-8791-9. E-book, can be ordered online: https://www.cengage.uk/c/custom/9781473787919/
R (open source software, download for free at www.r-project.org)
R Studio (open source software, download for free at www.posit.co)
Exercise book Experimental and Correlational Research 2024-2025.
Lecture slides (provided on Brightspace).
Please note: Pre-Master students might need additional literature and/or software for using SPSS and will be informed about this by the study adviser or the course coordinator.
Contact information
Drs. Hemmo Smit hsmit@fsw.leidenuniv.nl