MATH106
Download as PDF
MATH 106 - Mathematical Probability Theory
Course Title
Mathematical Probability Theory
Course Description
A rigorous development of the basics of modern probability theory based on a self-contained treatment of measure theory. The topics covered include: probability spaces; random variables; expectation; convergence of random variables and expectations; laws of large numbers; zero-one laws; convergence in distribution and the central limit theorem; Markov chains; random walks; the Poisson process; and discrete-parameter martingales.
Minimum Units
4
Maximum Units
4
Grading Basis
Default Letter Grade; P/NP Option
Method of Assessment
Written Exam
Prerequisites
Mathematics 104
Repeat Rules
Course is not repeatable for credit.
Credit Restriction Courses. Students will receive no credit for this course if following the course(s) have already been completed.
-
Credit Replacement Courses
-
Formats
Lecture
Term
Fall and Spring
Weeks
15 weeks
Weeks
15
Lecture Hours
3
Lecture Hours Min
3
Lecture Hours Max
3
Lecture Mode of Instruction
In Person
Outside Work Hours
9
Outside Work Hours Min
9
Outside Work Hours Max
9