MTH 535
Measure and Integration I

Course Information and Syllabus, Fall 2008

Text: Measure Theory and Probability by M. Adams and V. Guillemin, Wadsworth & Brooks, 1996 

Recommended reading:  

Royden, Real Analysis, 3rd ed. Prentice-Hall, 1988.

R. Wheeden and T. Zygmund, Measure and Integral: An Introduction to Real Analysis, CRC 1977


Prerequisites: Graduate standing, exposure to advanced calculus and basic course in probability

Exams and Grading:

Course grade will be determined based on homework and mid-term and final exams:

Homework:   50 %

Exams:          50 %

The exams will be of the take home variety.

The topics that will be covered are:

Basic Construction of Lebesgue Measure.  Lebesgue Integrals. Convergence in measure.  Various Limiting Theorems.

Application of Measure and Integration Theory to Probability Theory: Random Variables and Expectations. Laws of Large Numbers.


Computer Requirements

The use of computer algebra systems such as MATHEMATICA, MAPLE, and Scientific Notebook is encouraged.  Some of the problems may need MAPLE or MATHEMATICA to be solved effectively.

Instructor: Dr. M. Kulenovic,
Phone: 44436
Online information: or

Office: Tyler 216/ Lippit 200
Office hours: MW 1-2, F 10-11 and by appointment. 

Time: MW 3-4:15
Place: Tyler Hall 106

Useful links:

Measure Theory at Harvard University

Prof. Kaskosz course in Measure Theory