Description
Introduction to the theory of probability. Discrete and continuous random variables, expectation, and variance. Independent random variables, conditional probability, and Bayes Theorem. Discrete and continuous probability distribution functions, including joint distribution functions. One-variable and two-variable statistical measures and hypothesis testing. Applications of statistics in computing. This course may contain group work at the discretion of the instructor.
Learning Hours
120 (36 Lecture, 84 Private Study)
Prerequisite
Registration in a Bachelor of Computing Program.
Corequisite
CISC 101/3.0 or CISC 102/3.0 or CISC 121/3.0.
Exclusion
Maximum of one course from: BIOL 243/3.0; CHEE 209/3.5; CISC 171/3.0; COMM 162/3.0; ECON 250/3.0; GPHY 247/3.0; HSCI 190/3.0; KNPE 251/3.0; NURS 323/3.0; POLS 285/3.0; POLS 385/3.0*; PSYC 202/3.0; SOCY 211/3.0; STAM 200/3.0; STAT 161/3.0; STAT 263/3.0.