Contents
- 7.1 Detecting the Martian invasion
- 7.2 Quantifying prior belief
- 7.3 Using Bayes Theorem
- 7.3.1 Bayes for intelligent interfaces
- 7.3.2 Making decisions – base rates, risk and error costs
- 7.4 Bayes as a statistical method
- 7.5 How do you get the prior?
- 7.6 Handling multiple evidence
- 7.7 Internecine warfare
Glossary items referenced in this chapter
artificial intelligence, base rate, base rate neglect, Bayes factor, Bayes rule, Bayesian reasoning, Bayesian statistics, Cauchy distribution, cognitive bias, coin tossing, conditional probability, confidence interval, confirmation bias, default Bayesian factors, encoding (belief) as probability, error costs, error rate, fair coin, false negative, false positive, hypothesis testing, independence, independent evidence, intelligent interfaces, Kolomogrov laws, likelihood, machine learning, mathematics, Normal distribution, null hypothesis, odds ratio, optimal decision, p-value, population base rate, positive results, posterior distribution, presentation base rate, prior belief, prior distribution, quantified belief, random effect, real world, representative sample, risk, sample base rate, significance level, stakeholders, statistical analysis, statistical inference, stratified sample, task completion time, the job of statistics, traditional statistics, unbounded data, uniform prior