Covers risk and uncertainty in environmental projects, focusing on cost-benefit analysis and the concept of certainty equivalent for risk-averse individuals.
Explores Bayesian techniques for extreme value problems, including Markov Chain Monte Carlo and Bayesian inference, emphasizing the importance of prior information and the use of graphs.
Explores verification and validation in computational modeling, emphasizing accuracy through comparison with experimental data and practical advice on model complexity.
Explores levels of analysis in social psychology and critical thinking, emphasizing cognitive dissonance and the importance of skepticism in decision-making.