MATH 402 Measure Theory and Probability (Not offered 1997-98)
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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 apply them to probability spaces. Included will be Lebesgue 
and Borel measures, measurable functions (random variables), Lebesgue integration, 
distributions, independence, convergence and limit theorems. Also included 
will be an introduction to Lp-spaces. This material provides excellent preparation 
for graduate school.
Evaluation will be based primarily on performance on homework assignments and 
exams.
Prerequisite: Mathematics 301 or 305, or permission of instructor.
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	O. BEAVER
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