Statistical inference in a wide range of problems at an advanced level. It covers the general theory of estimation, tests and confidence intervals by deriving in particular the asymptotic properties of the maximum likelihood estimator and the likelihood ratio, Wald, and scores tests (and their generalizations) and the calculus of M-estimation. Selected modern topics such as Bayesian and permutation inference, rank tests, the jackknife, and the bootstrap.