This course covers probability including its role in statistical and computational modeling. Topics include classical and computational perspectives on cumulative, mass and distribution functions, random variables, expectation, limiting results, the normal distribution. Computational topics include generating and sampling random numbers, combinatorial objects and probability functions for simulation and statistical analysis. Additional techniques include resampling, hypothesis testing, model fit and cross validation. IMPORTANT NOTE: STA246H5 will not be permitted as a pre-requisite for any other 200+ level STA courses. In addition, STA246H5 cannot count towards any program(s) in Mathematics or Applied Statistics. The course is intended only for students in Computer Science programs who will not need STA256H5 for other program requirements.