This course covers probability spaces as models for phenomena with statistical regularity.
- Prathapa Kaluwa Devage Instructor, Statistics
- Axioms, properties and conditional probability
- Discrete spaces (binomial, hypergeometric, and Poisson)
- Continuous spaces (normal, exponential) and densities
- Random variables, expectation, independence and conditional probability
- Laws of large numbers and central limit theorem
3.0 - 5.0
Integral Calculus of Several Variables (Stanford Course: MATH 52) and familiarity with infinite series, or equivalent.