TMA4265 Stochastic Processes, Autumn 2013

Lecture plan

This schedule is tentative, changes will appear.

R = Ross, Introduction to probability models, 10th edition, Academic Press

Week	Topics	Reading
34	21.08	Review: Probability and random variables	R: Ch. 1 and 2
	22.08	Exercises: Introduction to R
	23.09	Review: Probability and random variables	R: Ch. 1 and 2
35	28.08	Conditional expectation	R: Ch. 3.1, 3.2, 3.3
	30.08	Conditional expectation	R: Ch. 3.4, 3.5
36	04.09	Conditional expectation	R: Ch. 3.6, 4.1
	06.09	Markov chains	R: Ch. 4.2, 4.3
37	11.09	Markov chains	R: Ch. 4.3
	13.09	No lecture, exercise work
38	18.09	Markov chains	R: Ch. 4.4
	20.09	Markov chains	R: Ch. 4.4
39	25.09	Markov chains	R: Ch. 4.4, 4.5.1
	27.09	Markov chains	R: Ch. 4.6, 4.7
40	02.10	Markov chains	R: Ch. 4.7, 4.8
	04.10	Markov chain	R: Ch. 4.8, 4.9
41	09.10	Poisson process	R: Ch. 5.1, 5.2
	11.10	Poisson process	R: Ch. 5.3
42	16.10	Project (Nullrommet 380A)
	18.10	Project (No lecture)
43	23.10	Poisson Process	R: Ch. 5.3
	25.10	Markov chains	R: Ch. 6.1, 6.2, 6.3
44	30.10	Markov chains	R: Ch. 6.3,6.4
	01.11	Markov chains	R: Ch. 6.4
45	06.11	Markov chains	R: Ch. 6.5
	08.11	Markov chains & Queueing Theory	R: Ch. 6.6, Ch. 8.1, 8.2, 8.3.1
46	13.11	Queueing Theory	R: Ch. 8.3.2, 8.3.4
	15.11	Queueing Theory	R: Ch. 8.3.5, 8.5
47	20.11	Queueing Theory	R: Ch. 8.9.1, 8.9.2
	22.11	Brownian motion	R: Ch. 10.1, 10.3