STAT 2655
Introduction to Probability with Applications (Honours)
Probability axioms, basic combinatorial analysis, conditional probability and independence, discrete and continuous random variables, joint and conditional distributions, expectation and moments, probability and moment generating functions, Chebyshev's inequality and weak law of large numbers, central limit theorem, sampling distributions, simulation and applications to descriptive statistics.
2022
Topics
- Introduction/
- 2.1, 2.2, 2.3, 2.4, 2.5, 2.6
- 2.7, 2.8, 2.9, 2.10
- 2.11, 3.1, 3.2, 3.3, 3.4, 3.5
- 3.6, 3.7, 3.8, 3.9
- 4.1, 4.2, 4.3, 4.4, 4.5
- 4.6, 4.7, 4.9, 4.10, 3.11
- – Nov 4 5.1, 5.2, 5.3, 5.4, 5.5
- 5.5, 5.6, 5.7, 5.8, 5.11
- 5.9, 5.10, 6.1. 6.2
- 6.3, 6.4, 6.5
- – Dec 2 6.6, 7.1
- – Dec 9 7.2, 7.3, 7.5
Readings
- Mathematical Statistics with Applications, 7th Edition, Wackerly, Mendenhall, and Scheaffer.
Prerequisites & course information
Precludes additional credit for STAT 2605 . Prerequisite(s): MATH 2052 with a grade of C+ or higher or MATH 2007 or MATH 1005 with a grade of B+ or higher; and MATH 2152 with a grade of C+ or higher or MATH 2107 with a grade of B+ or higher; or permission of the School. Lectures three hours a week, tutorial one hour a week.
Sources
- Course catalogue ↗2026–2027
- STAT 2655A F22 ↗2022