Probability Theory
       Probability Theory Fundamentals: About this section
       Frequentist approach to probability
       Bayesian approach to probability
       Probability axioms
       Variables and probability distributions
       Joint events and marginalisation
       Conditional probability
       Bayes rule
       Bayes Rule Example
       Likelihood Ratio
       Chain rule
       Independence and conditional independence
       Biases and fallacies in reasoning about probability
             Biases and fallacies in reasoning about probability: about this section
             Denial of Uncertainty
             Adjustment of uncertainty
             Conjunction Fallacy
             Hindsight bias
             Fallacies associated with causal and diagnostic reasoning
What is a Bayesian network?
       What is a Bayesian network?
BBNs: a detailed account
       BBN Tutorial: About this section
       Definition of BBNs: graphs and probability tables
       Analysing a BBN: entering evidence and propagation
       The notion of 'explaining away' evidence
       Why do we need a BBN for the probability computations?
       General case of joint probability distribution in BBN
       What happens when the number of variables increases?
       In summary: why should we use BBNs?
       How BBNs deal with evidence: about this section.
       Serial Connection
       Diverging connection
       Converging connection
       The notion of d-separation
BBNs and Bayesian Probability Resources
       BBNs and Bayesian Probability Resources: Overview
       Probability References
       References on eliciting probabilities
       Books about BBNs
       Papers about BBNs
       BBN related web sites
       BBN tools
       Relevant Journals for BBNs
       People working on BBNs