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This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.
Table des matières
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.
A propos de l'auteur
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.
Résumé
Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers' knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data.
