Vue d'ensemble
G茅nie 茅lectrique : The basic probability model, the heuristics of model-building and the additivity of probability; classical models; conditional probability and Bayes rule; random variables and vectors, distribution and density functions, expectation; statistical independence, laws of large numbers, central limit theorem; introduction to random processes and random signal analysis.
Terms: Automne 2009, Hiver 2010
Instructors: Champagne, Benoit (Fall) Caines, Peter Edwin (Winter)
- (3-1-5)
- Prerequisite: ECSE 303 or ECSE 306.
- Tutorials assigned by instructor.