Week 1

• 1.1 Two Components of an Analysis

• 1.2 Reversing Conditioning

• 1.3 Idiot Bayes

• 1.4 Bayes Learning

Week 2

• 1.5 Bayes rule in court

• 1.6 Decisions can change distributions!

• 2.1 Decision trees

• 2.2 Expected value of information

• 2.3 Some Practical Issues

Week 3

• 3.1 Utilities and Rewards

• 3.2 Utility and the value of money to you

Week 4

• 3.3 Utility Elicitation (1D)

• 3.4 Decision Making with Continuous Variables

• 4.1 Multiattribute Utility Theory

Week 5

• 4.2 Value Independent Attributes

• 4.3 Decision Conferencing and Utility Elicitation

• 4.4 Real Time Support within Decision Processes

Week 6

• 5.1 Calibration and probability prediction

• 5.2 Normal form analysis

Week 7

• 6.1 Relevance and Bayesian Networks

• 6.2 Bayesian Networks & Graphs

Week 8/9

• 6.3 Decomposable Graphs and Propagation

• 6.4 An Example of Propagation

Week 10

• 7.1 Updating Probabilities — Prior to Posterior Analyses

• 7.2 Binomial Experiments

• 7.3 Updating Multinomial Probabilities