2023-2024 / PSYC4027-1

Strength analysis in experimental and clinical research


30h Th

Number of credits

 Master in psychology (120 ECTS)3 crédits 


Etienne Quertemont, Ezio Tirelli


Ezio Tirelli

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

- Meta-research and scientific methodology
- The publication bias
- Questionable research practices (QRPs) and the lack of methodological quality
- The basic logic of the NHST statistical inference
- P-hacking and other conscious or unconscious bias (or QRPs)
- Effect size, sample size and statistical power
- False-positives inflation and the decline effect
- Replications and irreproducibility of the scientific results
- Pseudo-replications and experimental or observational units
- Randomization and blinding procedures
- Neglected experimental designs that favor power
- Basic introduction to the software G*Power

Learning outcomes of the learning unit

- Critical reasoning and statistical thinking
- Better knowledge of the "scientific behaviors"
- Ethical aspects of scientific research

Prerequisite knowledge and skills

Basics in psycho-statistics, psychometrics and experimental psychology and possibly an overall view of the contemporary scientific disciplines.

Planned learning activities and teaching methods

Analysis of publications in the fields of meta-research and scientific methodlogy.

Mode of delivery (face to face, distance learning, hybrid learning)

The participation of the student is necessary.

Recommended or required readings

A number of recent and classical papers will be provided by the teacher.
Recommended reading: 
Chambers C.  The 7 deadly sins of psychology.  Princeton University Press.
Some suggested important titles:
Kirk RE. Experimental design: Procedures for the behavioral sciences. New York: Sage, 2012.
Kline RB. Behond significance testing. Washington DC: APA, 2013.
Makel MC & Plucker JA (eds) Toward a more perfect psychology. Washington DC: APA, 2017.
Motulsky H. Intuitive biostatistics: A nonmathematical guide to statistical thinking. Oxford University Press, 2014.
Williams M, Curtis MJ, & Mullane K (eds) Research in the biomedical sciences: Transparent et reproducible. London: Academic Press, 2018.

Any session :

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )

- Remote

written exam ( multiple-choice questionnaire, open-ended questions )

- If evaluation in "hybrid"

preferred in-person

Additional information:

Written examination/test.

Work placement(s)

Possible. To be decided separately.

Organisational remarks and main changes to the course




Association of one or more MOOCs