Important:

These documents are provided as a convenience only. They are not meant to replace the lectures as given in class, which often contain important clarifications and/or corrections. Please do not try to use them as a substitute for attending classes.

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lecture1  

lecture2

lecture3

lecture4
 
lecture5

(note the overlap with lecture4)

lecture6

(note the overlap with lecture5)

lecture7

This lecture includes the class notes of October 30, an alternative derivation of the independence of the sample mean and variance when sampling from a normal, and a few more details of the normal random vector. It is important that you understand this lecture (all of it) before the next lecture).

lecture8

This lecture provides further details of the distinguishable versus non-distinguishable situations in point processes. It also covers proofs of the CLT and WLLN's. Basic convergence concepts are covered including a proof of the Lebesgue Dominated Convergence Theorem (DCT) and the use of subsequences convergence problems is explored. A proof of the Borel-Cantelli Lemma is not included. It may be found in the assigned problems.

lecture9



lecture10

This is the on-line version of the November 20th lecture (and part of the very last lecture). You are not responsible for this for the test. Problems related to this lecture will be posted November 27 after the test. It is a very brief discussion of the renewal theorem, simple random walk and  Markov Chains (including Poisson processes and Galton Watson Branching Processes).

Part of the in-class lecture will review convergence problems. You will be responsible for that material on the test.