Class Schedule

M 11/4	Grinstead and Snell 7 Gravner notes 8	More on Expectation and Variance of Sums of Random Variables CLT
W 11/6		Markov Chains
F 11/8	Midterm 2 due at beginning of class	Markov Chains
M 11/11		Special Topics
W 11/13	Groups 1,3, 5, 9, 10,	Begin Group Presentations
F 11/15	2, 4, 6, 7, 8	Finish Group Presentations

Day and Date	Suggested Readings and Practice Problems	Notes and Announcements
M 9/16	G&S 1.2	What is Probability?
T 9/17 (x-hour)		Proof writing techniques
W 9/18	G&S 3.1	Combinatorics HW 1 assigned
Th 9/19
F 9/20	G&S 3.2	More combinatorics
M 9/23	Continue G&S Chapter 3 Chapter 3 & 4 of Gravner's notes	Axioms of Probability
T 9/24 (x-hour)		Groups assigned for project
W 9/25		Conditional Probability HW 1 due at beginning of class HW 2 assigned
F 9/27	G&S Chapter 4	More Conditional Probability
M 9/30	G&S Chapter 4 and 5 and back to 1.2 Gravner Notes Chapter 5	Independent and Dependent events
T 10/1		Project rubric
W 10/2		Random Variables HW 2 Due HW 3 assigned
F 10/4		More RVs
M 10/7	Gravner Notes Chapter 5 Grinstead and Snell 5.1	Expectation and Variance
T 10/8		Midterm 1
W 10/9		Common distributions and their properties
F 10/11	Gravner notes 5.3	Inequalities HW 3 due HW 4 assigned
M 10/14	Gravner notes 5.5	Geometric Distribution
W 10/16	Grinstead and Snell Chapter 8	Markov's Inequality Chebyshev's Inequality
F 10/18	Gravner notes 5.6	Poisson Distribution HW 4 due HW 5 assigned
M 10/21	Gravner notes 6	Continuous Random Variables
M 10/23		More continuous RVs and common continuous distributions
F 10/25		More distributions HW 5 due HW 6 Assigned
M 10/28	Grinstead and Snell 7 Gravner notes 8	Sums of Random Variables
M 10/30		Weak and Strong Law of Large Numbers
F 11/1		Central Limit Theorem HW 6 due