Dix Statistics for HCI

Making Sense of Quantitative Data
1. Auflage 2022
ISBN: 978-3-031-02228-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 161 Seiten, Web PDF

Reihe: eBColl Synthesis Collection 9

Many people find statistics confusing, and perhaps even more confusing given recent publicity about problems with traditional p-values and alternative statistical techniques including confidence intervals and Bayesian statistics. This book aims to help readers navigate this morass: to understand the debates, to be able to read and assess other people's statistical reports, and make appropriate choices when designing and analysing their own experiments, empirical studies, and other forms of quantitative data gathering.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Dix, Alan

Inhaltsverzeichnis

Preface.- Acknowledgments.- Introduction.- The unexpected wildness of random.- Properties of randomness.- Characterising the random through probability distributions.- Probing the unknown.- Traditional statistics.- Bayesian methods.- Common issues.- Differences and distinctions.- Gaining power -- the dreaded `too few participants'.- So what? --- making sense of results.- Moving forward: the future of statistics in HCI.- Bibliography.- Author's Biography.- Index .

Über Autor(innen)

Alan Dix is the Director of the Computational Foundry, Swansea University, Wales. 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 data processing. More recent work includes community engagement, especially in rural areas, 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, including representing the UK in the International Mathematical Olympiad. He has practised 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 visualisation 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 unique insight into the challenges and problems of applying statistics to HCI data.