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Doing Better Statistics in Human-Computer Interaction

$36.99 (P)

  • Date Published: March 2019
  • availability: In stock
  • format: Paperback
  • isbn: 9781108710596

$ 36.99 (P)

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About the Authors
  • Each chapter of this book covers specific topics in statistical analysis, such as robust alternatives to t-tests or how to develop a questionnaire. They also address particular questions on these topics, which are commonly asked by human-computer interaction (HCI) researchers when planning or completing the analysis of their data. The book presents the current best practice in statistics, drawing on the state-of-the-art literature that is rarely presented in HCI. This is achieved by providing strong arguments that support good statistical analysis without relying on mathematical explanations. It additionally offers some philosophical underpinnings for statistics, so that readers can see how statistics fit with experimental design and the fundamental goal of discovering new HCI knowledge.

    • Readers do not have to struggle with mathematics in order to understand the arguments around how to do better statistics
    • Provides the underpinning philosophy of statistics in science
    • Allows readers to quickly find the answers they seek within the concise chapters
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    Reviews & endorsements

    'If you, and your experiments, have been bruised by statistical misfortune, then this is the book for you. Paul Cairns' wise and pragmatic advice talks us through the practical use of statistics in Human-Computer Interaction, showing his own bruises when necessary. This should become the standard reference that the field needs.' Alan Blackwell, University of Cambridge

    'In Human-Computer Interaction, we gather data from experiment designs that are often more complex or messy than those presented as examples in a basic textbook on statistics. Cairns presents digestible information for an interdisciplinary audience with expertise and authority. I will be buying a copy of this book for my students, and also one for myself!' Regan Mandryk, University of Saskatchewan, Canada

    'This is a must-read for novice or well-established researchers alike, who are worried about whether they are conducting the correct statistical analyses of their data. Paul Cairns makes learning about statistics seem both fun and interesting. I'm confident that this book will positively impact the quality of future Human-Computer Interaction research.' Anna L. Cox, University College London Interaction Centre

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    Product details

    • Date Published: March 2019
    • format: Paperback
    • isbn: 9781108710596
    • length: 250 pages
    • dimensions: 227 x 151 x 13 mm
    • weight: 0.36kg
    • contains: 29 b/w illus. 7 tables
    • availability: In stock
  • Table of Contents

    Getting started
    Part I. Why We Use Statistics:
    1. How statistics support science
    2. Testing the null
    3. Constraining Bayes
    4. Effects: what tests test
    Part II. How To Use Statistics:
    5. Planning your statistical analysis
    6. A cautionary tail: why you should not do a one-tailed test
    7. Is this normal?
    8. Sorting out outliers
    9. Power and two types of error
    10. Using nonparametric tests
    11. A robust t-test
    12. The ANOVA family and friends
    13. Exploring, over-testing and fishing
    14. When is a correlation not a correlation?
    15. What makes a good Likert item?
    16. The meaning of factors
    17. Unreliable reliability: the problem of Cronbach's alpha
    18. Tests for questionnaires.

  • Author

    Paul Cairns, University of York
    Paul Cairns is a reader in Human-Computer Interaction at the University of York and Scholar-in-Residence for The AbleGamers Charity that helps people with disabilities combat social isolation by making videogames more accessible. He has taught statistics at all levels of education for nearly twenty years. His particular research interest is in players' experiences of digital games, and his expertise in experimental and statistical methods was developed through working in this area.

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