MATH 402 Spring 2013 Measure Theory and Probability (Q)

The study of measure theory arose from the study of stochastic (probabilistic) systems. Applications of measure theory lie in biology, chemistry, physics as well as in economics. In this course, we develop the abstract concepts of measure theory and ground them in probability spaces. Included will be Lebesgue and Borel measures, measurable functions (random variables). Lebesgue integration, distributions, independence, convergence and limit theorems. This material provides good preparation for graduate studies in mathematics, statistics and economics.
Class Format: lecture/discussion
Requirements/Evaluation: evaluation will be based primarily on performance on homework assignments and exams
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Prerequisites: Mathematics 301 or 305 or permission of instructor
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Divisional Attributes: Division III,Quantitative and Formal Reasoning
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Class Number: 3233
CLASSES ATTR INSTRUCTORS TIMES CLASS NUMBER ENRL CONSENT
MATH402-01(S) LEC Measure Theory and Probablity (Q) Division 3: Science and MathematicsQuantitative and Formal Reasoning Frank Morgan
MWF 11:00 AM-11:50 AM Bronfman 107 3233
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