STATS 2D03

INTRODUCTION TO PROBABILITY

Undergraduate

Spring/Summer 2026 · Intro To Probability · C01

Readings

Etext Introduction To Probability - 6 Month Access
Anderson · Required
ISBN 9781108246705; 9781108415859

Spring/Summer 2026 · C01

Counting and sampling, binomial coefficients, counting problems
Set theory notation, probability spaces, equally likely outcomes, infinite sample spaces
Inclusion-exclusion principle, discrete random variables, conditional probability, law of total probability, Bayes' theorem, independence
Independent trials, geometric and binomial distributions, Polya's urn, continuous random variables, PDFs, CDFs, uniform distribution
Victoria Day: No Lecture
Expected value, properties of the expected value, expected value of a function of a random variable, variance, geometric & exponential memorylessness property
Midterm 1
Normal approximation to the binomial, inequalities and the weak law of large numbers, Poisson approximation to the binomial
Functions of a random variable, joint distributions of dependent discrete random variables
Jointly continuous random variables, independence in joint distributions, covariance and correlation
Midterm 2
Moment generating functions, sums of independent random variables, convolutions

Introduction to Probability
David F. Anderson, Timo Seppäläinen, Benedek Valkó · 20171102 · 1 · Required
Cambridge University Press · ISBN 9781108246705
Introduction to Probability ISBN: 9781108246705 Authors: David F. Anderson, Timo Seppäläinen, Benedek Valkó Publisher: Cambridge University Press Publication Date: 20171102 Edition: 1
See source
Appendix C & D;1.2
See source

Fall 2026 · Intro To Probability · C01, C02

eText Introduction To Probability - Lifetime Access
Balakrishnan · Immediate Access
ISBN 9781118548493; 9781118548714

Fall 2025 · Intro To Probability · C01, C02

Etext Introduction To Probability - 6 Month Access
Anderson · Required
ISBN 9781108246705; 9781108415859

Sources