In this course we will study basic topics in modern statistical inference. This will include traditional concepts of mathematical statistics: likelihood estimation, method of moments, properties of estimators, exponential families, decision-theory approach to hypothesis testing, likelihood ratio test as well as more recent approaches such as Bayes estimation, Empirical Bayes and nonparametric estimation. During the computer classes (using R software package) we will illustrate the various estimation techniques and give an introduction to computationally intensive methods like Monte Carlo, Gibbs sampling and EM-algorithm.
Three 1 hour lectures, one 1 hour tutorial and one 1 hour computer laboratory per week.
One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%)
STAT2X11 and (DATA2002 or STAT2X12)Prohibitions
STAT3913 or STAT3001 or STAT3901