Statistics for HCI
Autor Alan Dixen Limba Engleză Hardback – 27 feb 2027
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Specificații
ISBN-10: 3032352797
Pagini: 288
Ediția:Second Edition 2026
Editura: Springer Nature Switzerland AG
Notă biografică
Alan Dix is an Emeritus Professor at Cardiff Metropolitan University and at Swansea University, Wales, where he was previously Director of the Computational Foundry. He is well known for an HCI textbook and research in HCI including CSCW, mobile interfaces, technical creativity and some of the earliest work on privacy and the ethical implications of intelligent algorithms. More recent work includes community engagement, especially in rural areas, renewed work on the boundaries between HCI and AI, and his thousand-mile research walk around Wales, which generated substantial quantitative and qualitative open research data, from blogs to biodata. Before he was in HCI, Alan was a mathematician and represented the UK in the International Mathematical Olympiad. He has practiced as a professional statistician and applied mathematician including work on modelling agricultural crop sprays, medical statistics and undersea cable detection. Within HCI these skills have been applied in his foundational work on formal methods for interactive systems, the use of Bayesian techniques in education, random sampling for visualization of big data and uncertainty, and analysis of potential bias against human/applied areas in REF, the UK research assessment exercise.
This unusual combination of skills and experience gives Alan a unique insight into the challenges and problems of applying statistics to HCI data.
Cuprins
Preface.- Introduction.- PART I: Wild and Wide—Concerning Randomness and Distributions.- The unexpected wildness of random.- Properties of randomness.- Characterizing randomness through probability distributions.- PART II: Doing It—If Not p Then What.- Probing the unknown.- Traditional statistics.- Bayesian methods.- Statistical Methods Interacting with AI and ML.- Common issues.- Differences and distinctions.- PART III: Going Large—Computation, Big Data, and AI.-Empirical and Simulation Methods: Beyond Fixed Tests.- Big Data: Seeing Through the Forest.- AI: Intelligence But Not as We Know It.- PART IV—Design and Interpretation.- Gaining power: The dreaded `too few participants'.- So what?: Making sense of results.- Moving forward: The future of statistics in HCI.