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MATH 307 - Applied Linear Algebra

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Lecture topics

Topics covered in each lecture will be listed below, with relevant chapter in the book. Many other books and lecture notes on probability are available, and may be helpful. These can be found in the library or online.

Ch. 4
Date Chapter Notes Topics
01-09 N/A PDF Counting
01-11 Ch. 1 PDF probability definition
01-13 Ch. 1 PDF Birthday asymptotics, properties of probability
01-16 Ch. 1 PDF Conditional probability, Independent events
01-18 Ch. 1 PDF Law of total probability, Bayes formula
01-20 Ch. 2 PDF Random Variables
01-23 Ch. 2 PDF More Random Variables, expectation
01-25 Ch. 2 PDF Expectation of discrete RVs, continuous RVs definition, exponential
01-27 Ch. 2 PDF Normal distribution, expectation of continuous RVs
01-30 Ch. 2 PDF Expectation, moments
02-01 Ch. 2 PDF Joint distribution, Marginals
02-03 Ch. 2 PDF Covariance
02-13 Ch. 2.7 PDF Law of Large Numbers
02-15 Ch. 2.7 PDF Central limit theorem
02-17 N/A PDF midterm
02-27 Ch. 2.7 PDF some statistics
02-27 Ch. 2.7 PDF some statistics
03-01 Ch. 2.7 PDF hypothesis testing, confidence intervals
03-03 Ch. 3 PDF Conditional distribution and expectation
03-06 Ch. 4 PDF Gambler's ruin, transience and recurrence
03-08 Ch. 4 PDF random walks in dim d
03-10 Ch. 4 PDF Random walks
03-13 Ch. 4 PDF general Markov chains basics
03-15 Ch. 4 PDF general Markov chains - cont.
03-17 Ch. 4 PDF general Markov chains - classification of states
03-20 Ch. 4 PDF general Markov chains - recurrence, stationary dist.
03-22 Ch. 4 PDF time reversal and reversibility
03-24 Ch. 4 PDF Reversibility
03-27 PDF Reversibility
03-29 Ch. 4 PDF Reversibility applications
03-31 Ch. 4 PDF First step analysis
04-03 Ch. 4 PDF First step analysis, branchnig processes
04-03 Ch. 4 PDF branching processes, Markov Chain Monte Carlo