Handbook

The course introduces theoretical concepts used in classical and modern statistics. MATH2801 is the entry-point for a statistics major and a prerequisite for most higher-level statistics courses. Topics covered include probability, random variables, standard distributions, bivariate distributions, transformations, central limit theorem, sampling distributions, point estimation, interval estimation, maximum likelihood estimation and hypothesis testing. Students will use the (free) statistics package R/RStudio. Lecture content will be delivered either in-person or online and will be recorded and made available online. Tutorials will be either in-person or online.

Note: The Assumed Knowledge is first year probability theory and integration. Probability theory revision notes will be made available online and some exercises will be revised briefly in the first tutorial. MATH2801 is compulsory for mathematics majors to ensure an introduction to statistics as a discipline for studying stochastic (random) systems, as opposed to the deterministic. MATH2901 (Higher Theory of Statistics) is a more theoretical/advanced version of MATH2801 which spends more time on proof and theoretical considerations.