Python for Experimental Psychologists

A Fun Way of Learning How to Code Your Experiments and Analyses
2. Auflage 2024
ISBN: 978-1-032-00480-8
Verlag: Taylor & Francis

Buch, Englisch, 200 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 522 g

Python for Experimental Psychologists equips researchers who have no prior programming experience with the essential knowledge to independently script experiments and analyses in the programming language Python. This book offers an excellent introduction, whether you are an undergraduate, a PhD candidate, or an established researcher.

This updated edition is on Python 3 (the most current version). It starts by teaching the fundamentals of programming in Python and then offers several chapters on scripting experiments (displaying stimuli, obtaining and logging user input, precision timing, etc.) using the popular PsychoPy package. The remainder of the book is dedicated to data analysis and includes chapters on reading/writing to text files, time series, eye tracking, data visualisation, and statistics.

Access to online support material enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. This book assumes no prior knowledge, and its informal and accessible tone helps readers with backgrounds in experimental psychology and cognitive neuroscience to quickly understand Python. It serves as a useful resource not only for researchers in these fields but also for lecturers instructing on methodology and data analysis.

Python for Experimental Psychologists demystifies programming complexities and empowers researchers to proficiently conduct experiments and analyse their results.

Zielgruppe

Postgraduate, Professional, and Undergraduate

Autoren/Hrsg.

Dalmaijer, Edwin S

Hirst, Rebecca

Peirce, Jonathan

Fachgebiete

• Sozialwissenschaften Psychologie Psychologie / Allgemeines & Theorie Psychologische Forschungsmethoden
• Sozialwissenschaften Psychologie Allgemeine Psychologie Biologische Psychologie, Neuropsychologie
• Sozialwissenschaften Psychologie Psychologie / Allgemeines & Theorie Experimentelle Psychologie
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie

Inhaltsverzeichnis

About this book
About Python
About the authors

1. Python
2. Variable Types
Make Some Noise
Random Numbers
3. Creating and Presenting Stimuli
4. Processing Responses
Make Some Noise
5. Scripting An Experiment
Make Some Noise
6. Analysing Behavioural Data
7. Analysing Traces
8. Eye Tracking
9. Common Statistical Tests

Getting Help
Acknowledgements
References

Über Autor(innen)

Edwin S. Dalmaijer is a Lecturer (Assistant Professor) at the University of Bristol. He holds a DPhil from the University of Oxford, was a postdoc at the University of Cambridge, and has authored Python libraries, standalone software packages, teaching materials, and research articles.

Rebecca Hirst is Science Officer at Open Science Tools and Postdoctoral Researcher at Trinity College Dublin. She completed her undergraduate in Psychology and Cognitive Neuroscience and MSc in Psychology Research Methods at the University of Nottingham, where she then obtained a PhD in Psychology.

Jon Peirce is a neuroscientist, programmer, and dad. He holds an undergraduate in Psychology from St Andrews University, and a PhD in Neuroscience from the University of Cambridge. He is also the founder and CEO of Open Science Tools.