Description: The course studies various modes of convergence such as convergence in (i) distribution, (ii) probability, (iii) almost sure and (iv) $L_p$. Some relations and counter examples are discussed. Strong and weak laws of large numbers and the central limit theorem are studied and proved. Sigma fields and conditional expectation are also studied. Some tools needed to apply convergence in various statistical settings are discussed, such as Slutsky's Theorem and the Cramer-Wold device. The course is a non-measure theoretic introduction to these concepts.

Term: A

Course	Instructor(s)	Outline	Term	School Year
SS9657A001	Hao Yu		A	2018/2019
SS9657A001	Hao Yu		A	2016/2017
SS9657A001	Hristo Sendov		A	2015/2016
SS9657B001	Hristo Sendov		B	2014/2015
SS9657A001	Hao Yu		A	2013/2014
SS9657A001	Hao Yu		A	2012/2013
SS9657B001	Hao Yu		B	2011/2012