MATH5905 is a Mathematics Level V course. See the Course Overview below.

Units of credit: 6

Prerequisites: Math2801 or Math2901 or equivalent

Cycle of offering: once each year

Graduate attributes: the course will enhance your research, inquiry and analytical thinking abilities.

More information: this recent course handout (pdf) contains information about course objectives, assessment, course materials and the syllabus.

The Online Handbook entry contains up-to-date timetabling information.

This course provides a theoretical foundation for statistical inference. The three main goals in inference (estimation, confidence set construction and hypothesis testing) are discussed in decision theoretic framework. Emphasis is put on frequentist and Bayesian approaches.

Parametric, nonparametric and robust procedures are compared and contrasted. Optimality of inference is discussed for fixed sample size and in asymptotic sense. Higher order asymptotic methods are also introduced. Computationally intensive procedures such as the bootstrap are illustrated theoretically and numerically. Many illustrative examples and practical applications will be discussed.