Math 550 syllabus


Course Description: A comprehensive introduction to probability, the mathematical theory used to model uncertainty, covering the axioms of probability, random variables, expectation, classical discrete and continuous families of probability models, the law of large numbers and the central limit theorem. Credit for both MA 550 and MA 451 is not allowed.

Prerequisites:   C or better MA 227 or C or better in MA 237.

Suggested Textbook:   Mathematical Statistics with Applications, by Dennis D Wackerly, William Mendenhall and Richard L Scheaffer, Seventh Edition, Duxbury Press.
Course Coverage:   Chapters 1-7.

Learning outcomes:  The purpose of this course is to give students an introduction to probability theory and probability distributions. In particular, we will explore the axiomatic approach to probability, counting techniques, Bayes Theorem, random variables, probability distributions for discrete and continuous random variables, mathematical expectation, moment generating functions, joint and conditional distributions for multiple random variables, and measures of association (covariance and correlation), the law of large numbers and the central limit theorem.

Calculator:  A scientific calculator is required; the TI-89 is recommended.