George Mason University
Volgenau School of Engineering
Department of Statistics


STAT 544 Applied Probability

Fall Semester, 2015

Section 002

Thursdays from 7:20 to 10:00 PM (starting Sep. 3, other dates given below)

Location: room 1109 of Nguyen Engineering Building


Instructor: Clifton D. Sutton


Text:

A First Course in Probability, 9th Ed. , by Sheldon Ross (Prentice Hall, 2014)


Prerequisite:

three semesters of calculus and an undergraduate course covering calculus-based probability (like STAT 346)


Description:

This course covers elementary probability, reviewing concepts students should already have been exposed to and adding more details to what is typically covered in an undergraduate probability course. After covering simple combinatorics and the axioms of probability and some of their consequences, the course covers conditional probability, independence, random variables, common discrete and continuous distributions, joint distributions, expectation, limit theorems, and assorted other topics.

Approximate week-by-week content:

[1] Sep. 3:
combinatorics
[Ch. 1 of text]
[2] Sep. 10:
axioms of probability and some results which follow from them
[Ch. 2 of text]
[3] Sep. 17:
conditional probability and independence
[Sec. 3.1 through Sec. 3.3 of text, and some of Sec. 3.4]
[4] Sep. 24:
more on independence and conditional probability, discrete random variables
[Sections 3.4, 3.5, 4.1, and 4.2 of text]
[5] Oct. 1:
more on discrete random variables, expectation, discrete distributions based on iid Bernoulli random variables
[Sec. 4.3 through Sec. 4.6 of text]
[6] Oct. 8:
other discrete distributions and more results pertaining to random variables, Poisson processes, continuous random variables
[Sec. 4.7 through Sec. 4.10 of text, Sec. 9.1 of text, and Sec. 5.1 of text]
[7] Oct. 15:
1st Midterm Exam (on Ch. 1 through Ch. 3 (closed book and notes));
more on continuous random variables (including functions of cont. r. v's)
[Sec. 5.2 and Sec. 5.7 of text]
[8] Oct. 22:
common continuous distributions, and random variate generation
[Sec. 5.3 through Sec. 5.6 of text, and Ch. 10 through subsection 10.2.1 of text]
[9] Oct. 29:
joint distributions and independent random variables
[Sec. 6.1 through Sec. 6.3 of text]
[10] Nov. 5:
conditional distributions, order statistics
[Sec. 6.4 through Sec. 6.6 of text]
[11] Nov. 12:
2nd Midterm Exam (on Ch. 4 & Ch. 5 (open book and notes));
more on joint distributions, more on expectation
[Sec. 6.7 of text, and Sec. 7.1 & Sec. 7.2 of text]
[12] Nov. 19:
more on expectation, covariance and correlation
[Sec. 7.3 and Sec. 7.4 of text]
[**] Nov. 26:
no class due to Thanksgiving Break
[13] Dec. 3:
conditional expectation, moment generating functions
[Sec. 7.5 and Sec. 7.7 of text]
[14] Dec. 10:
more on expectation and normal random variables, limit theorems (and inequalities)
[Sec. 7.8 & Sec. 7.9 of the text, Sec. 8.1 through Sec. 8.4 of text]
[**] Dec. 17
Final Exam (note: exam period is from 7:30 to 10:15 PM)
Note: If any classes are cancelled due to bad weather (or for any other reason), some of the dates given above may be changed (including the dates for the exams).


Grading:


Additonal Comments: