Students seeking an introduction to the subject of Mathematical Statistics should take this course. Training in Mathematical Statistics is essential for would-be data scientists, actuarial scientists, market research statisticians, econometricians, risk analysts, statistical analysts to name but a few. Mathematics and Applied Mathematics 1 (MAM 101 and MAM 102) and Mathematical Statistics 102 are pre-requisites for Mathematical Statistics 2.
Mathematical Statistics may be taken as a major subject for BSc, BSc(InfSys), BCom, BEcon, BBusSc, BA or BSocSc degrees.
R and Rstudio are the primary computational software used and supported in the Department of Statistics at Rhodes University. Thank you to the R community for their support of the R project. We are very grateful that the DataCamp.com team assist our students learning by providing open access to their excellent courses.
The aims of this course are to acquaint students with:
• Combinatorial analysis: the basic counting principles; permutations and combinations.
• Random phenomena: sample spaces and events; the probability axioms; the probability of an event; random selection; probability rules; conditional probability; law of total probability and the theorem of Bayes; stochastic independence.
• Discrete stochastic variables: expected value; variance and moment-generating function of a stochastic variable.
• Important discrete distributions: binomial; Poisson, geometric; hyper-geometric; negative binomial.
• Joint probability mass functions; Marginal probability functions; Conditional discrete probability functions; Independent random variables.
Last Modified: Fri, 24 Jan 2020 09:21:35 SAST