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#
MATH 6280 3.0AF (Fall 2013)

*Measure Theory - Course outline
*

### Description:

Measure Theory is the basic language of probability theory and real analysis.
The Lebesgue spaces Lp are defined using measure theory, and these form the
key examples used in functional analysis.
This course is also one of the options for a comprehensive exam in the analysis stream of the PhD program, and is a core course for both the pure mathematics
and probability streams of the MA program.
### Prerequisites:

Undergraduate real analysis.

There are no Course Credit Exclusions.
### Course Webpage:

www.math.yorku.ca/~salt/courses/6280f13/6280.html
### Instructor/Contact Information:

Tom Salisbury
### Lectures:

MWF 11:30-12:20 in Chemsitry (CB) 122.
### Office hours:

Friday 12:30-1:30
I will try to post a notice on the course webpage if other commitments make
it necessary to reschedule.
If you can't make that time, you are welcome to e-mail or call
me to arrange an appointment at some other time.

### Text:

*Real Analysis* by Royden (and Fitzpatrick), 4th edition, Pearson 2010

We will cover large portions of chapters 2 - 4, 17 - 18, and 20. We
will cover some topics from 6-8 as well. You do not need to buy the text,
as the notes will be self contained. If I ask you to read additional topics
from the text, you can use the copy on reserve in Steacie library.
### Grading:

Note that the date given for the midterm is tentative
- 25% Assignments
- 25% Midterm exam (Tentatively Friday October 25)
- 50% Final exam