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Python for Experimental Psychologists: A Fun Way of Learning How to Code Your Experiments and Analyses 2nd edition [Kõva köide]

  • Formaat: Hardback, 186 pages, kõrgus x laius: 246x174 mm, kaal: 530 g, 8 Line drawings, black and white; 12 Halftones, black and white; 20 Illustrations, black and white
  • Ilmumisaeg: 11-Nov-2024
  • Kirjastus: Routledge
  • ISBN-10: 1032004800
  • ISBN-13: 9781032004808
Teised raamatud teemal:
  • Formaat: Hardback, 186 pages, kõrgus x laius: 246x174 mm, kaal: 530 g, 8 Line drawings, black and white; 12 Halftones, black and white; 20 Illustrations, black and white
  • Ilmumisaeg: 11-Nov-2024
  • Kirjastus: Routledge
  • ISBN-10: 1032004800
  • ISBN-13: 9781032004808
Teised raamatud teemal:
"Python for Experimental Psychologists equips researchers with no prior programming experience with the essential knowledge to independently script experiments and analyses, swiftly mastering Python. This updated edition navigates through programming fundamentals before delving into experimental scripting and data analysis. Aligned with the latest Python patch (Python 3), it illuminates techniques for displaying stimuli on computer screens, obtaining input from peripherals (e.g., keyboard, mouse), and interfacing with specialised equipment (e.g., eye trackers). Readers learn data logging and timing control alongside principles of basic and advanced data analysis, including trace data (e.g., pupil size) and gaze data analysis. Access to a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The book's informal and accessible tone deliberately targets aspects of Python pertinent to experimental psychologists and cognitive neuroscientists. It stands as a pivotal resource not only for researchers in these fields but also for lecturers instructing on experimentation and foundational data analysis. Python for Experimental Psychologists demystifies programming complexities, empowering researchers to proficiently execute experiments and analyse results, thus catalysing advancements in experimental psychology and cognitive neuroscience"--

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. The 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 a companion website enriches the learning experience with colour figures, example stimuli, datasets, scripts, and a portable Windows installation of Python. The 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 to analyse their results.



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. It offers an excellent introduction, whether you are an undergraduate, a PhD candidate or an established researcher.

Arvustused

'Programming in Python is an invaluable skill for psychology researchers, for both making experiments and analysing the resulting data.'

Christopher R Madan, author of Memories That Matter: How We Remember Important Things, Academia and the World Beyond book series on post-PhD careers, and An Introduction to MATLAB for Behavioral Researchers

Praise for previous edition

'An easy-to-read introduction. In a humorous style it introduces the reader to programming in Python, picking them up where they are as experimental psychologists. Very useful indeed!'

Ulrich von Hecker, Senior Lecturer, Cardiff University, UK

'Edwin Dalmaijer provides an intuitive introduction into psychological experimentation using Python libraries co-developed by the author himself. Well-structured and easy to read, this book will quickly have you programming, running and analysing your own experiments using open, modern tools.'

Tomas Knapen, Assistant Professor Cognitive Neuroscience, Vrije Universiteit Amsterdam, The Netherlands

'Python is fast becoming the lingua franca of scientific research, and this excellent and highly accessible book fills a much-needed gap for experimental psychologists. The strong focus on developing genuinely useful experimental code, and the comprehensive examples included, make it an outstandingly useful resource not just for students, but for seasoned researchers as well. Certainly the best (and funniest!) introduction to Python Ive come across.'

Matt Wall, Imaging Scientist, Imperial College London, UK

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

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.