

Probability, Statistics and Information  MATH2859  
Description Sample spaces, probability, random variables and probability distributions; examples of discrete and continuous distributions; Central Limit Theorem; statistical inference, confidence intervals and hypothesis testing; bivariate normal distribution, optimal mean square estimation, introduction to the multivariate normal distribution; linear regression and least squares estimation; inference in the linear model; online and offline estimation; statistical quality control; models, applications and statistical algorithms relevant to the fields of computer, electrical, software and telecommunications engineering.
Note: Available only to students for whom it is specifically required as part of their program. 