Statistics for HCI. Alan Dix
Probability can be hard –from goats to DNA
2.3.2 Tip: make the numbers extreme
3.2 Independence and non-independence
3.2.1 Independence of measurements
3.2.2 Independence of factor effects
3.2.3 Independence of sample composition
3.3.2 More (virtual) coin tossing
4 Characterising the random through probability distributions
4.1 Types of probability distribution
4.1.3 UK income distribution –a long tail
4.2.2 The central limit theorem –(nearly) everything is Normal
4.2.3 Non-Normal –what can go wrong?
4.2.5 Parametric and Nonparametric
PART II Doing It –If not p then What
5.1 Recall the job of statistics
6.1.1 The significance level –5 percent and all that
6.2.2 Important as well as significant?
7.1 Detecting the Martian invasion
7.3 Bayes for intelligent interfaces
7.3.1 Bayes as a statistical method
7.5 Handling multiple evidence
8.2.1 Non-independently controllable factors