Measure and Probability

The course introduces the MAT Selected Topics in Mathematics (3.0); 3 cr. The course student to the basic of measure theory, Lebesgue integration, probability spaces, random variables, sequences of random variables, almost sure convergence, weak convergence, conditioning on a sigma-field, martingales and martingales inequalities, and limiting distributions of random variables. MASTER DEGRE covers contemporary topics in Mathematics selected by the instructor. MAT 691 Master Thesis in Mathematics I; 3 cr. The research for the master thesis must show the student’s proficiency in approved topics in mathematics. Prerequisite: Advisor Consent. MAT 692 Master Thesis in Mathematics II; 3 cr. This course is a continuation of MAT 691. Prerequisites: MAT 691 and Advisor Consent.