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  • Python for Experimental Psychologists: A Fun Way of Learning How to Code Your Experiments and Analyses

    Python for Experimental Psychologists by Dalmaijer, Edwin S.; Hirst, Rebecca; Peirce, Jonathan;

    A Fun Way of Learning How to Code Your Experiments and Analyses

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    Rövid leírás:

    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.

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    Hosszú leírás:

    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.



    '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 careersand 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 I?ve come across.'


    Matt Wall, Imaging Scientist, Imperial College London, UK

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    Tartalomjegyzék:

    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

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