Fully funded PhD studentship: deep extreme value learning for landslide tail risk. Apply by 13 January 2027.
Term: Autumn / Semester 1. Offered in 2024.
Aims: to introduce the basic concepts of probability and statistics, and to illustrate their relevance to practical problem-solving.
Contents: set theory and counting problems; probability, including sample spaces, conditional probability, independence and Bayes' formula; discrete and continuous random variables, density and distribution functions, expectation and variance; introductory statistics, including sample statistics, unbiased estimators, the Central Limit Theorem and confidence intervals for the mean.
Term: Spring / Semester 2. Offered in 2025, 2026 and 2027.
Aims: to introduce rigorous mathematical tools useful in economic analysis, and to give students a solid mathematical background in game-theoretic models.
Contents: elements of a game; strategic and extensive games; Nash equilibrium; subgame-perfect equilibrium; backward induction; Bayesian Nash equilibrium; auctions; signalling games.
Term: Autumn / Semester 1. Offered in 2025 and 2026.
Aims: to introduce Bayesian statistics, to study posterior distributions and their properties, and to apply them to a range of data sets.
Contents: frequentist and subjective probability; prior, likelihood and posterior; conjugate priors; the Monte Carlo method; Markov chain Monte Carlo methods; applications.