Course Description
Probability axioms, combinatorial analysis, random variables, univariate and multivariate distributions, expectations, conditional distributions, independence, and laws of large numbers.
Additional Requirements for Graduate Students:
Additional theoretical problems will be assigned to graduate students.
Athena Title
INTRO PROBABILITY I
Equivalent Courses
Not open to students with credit in STAT 8170
Prerequisite
MATH 2500 or MATH 2270
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
This course is an introduction to probability theory at the advanced undergraduate or beginning graduate level. The course does not assume nor does it cover measure theory. The main course objectives are to give students an understanding of the fundamental ideas and theory of probability and to prepare them for further study in probability, statistics, and stochastic processes.
Topical Outline
Probability spaces, combinatorial analysis, discrete and continuous random variables, joint distributions, expectations, conditional distributions and conditional expectations, independence, moment generating and characteristic functions, the Central Limit Theorem, and laws of large numbers.