MA 261: Probability Models

Instructor: Arvind Ayyer
Office: X-15 (new wing)
Office hours: TBD
Phone number: (2293) 3215
Email: (First name) at iisc dot ac dot in
Class Timings: Mondays, Wednesdays and Fridays, 10:00 — 11:00
Classroom: LH-4 (new wing, first floor)
Textbook: Introduction to Probability Models (11th edition)
by Sheldon M. Ross
Academic Press, 2014
ISBN-13 - 978-9351072249

Supplementary Texts:
(a) Probability and random processes
by Geoffrey R. Grimmett and David R. Stirzaker
Oxford University Press, 2001
ISBN-13 - 978-0198572220

(b) Markov Chains and Mixing Times
by David A. Levin, Yuval Peres and Elizabeth L. Wilmer
Markov Chains and Mixing Times
ISBN-13 - 978-0812847398
TA:
  • Dipankar Roy (dipankarroy at iisc dot ac dot in)
Tutorials: Thursdays 9:30 — 10:00

Course Description

Sample spaces, events, probability, discrete and continuous random variables, Conditioning and independence,
Bayes' formula, moments and moment generating function, characteristic function, laws of large numbers,
central limit theorem, Markov chains, Poisson processes.

Prerequisites

Basic linear algebra and some exposure to proofs and abstract mathematics.

Exams

All exams will be closed book, closed notes, and
no calculators or electronic devices are allowed (no cell/smart phones).
No communication among the students will be tolerated.
There will be no make up exams.

The date for the midterms and final will be announced later.


Grading

Here are the weights for the homework and exams.
All marks will be posted online on Moodle.


Tentative Class Plan

Tutorials are marked in green.

week date sections material covered homework and other notes
1 2/8 1.1-1.2 Basic set theory Chap. 1: 1, 3, 4, 5, 6
2 5/8 1.3-1.4 Probabilities Chap. 1: 8, 11, 12, 13, 15, 19, 21
7/8 1.5-1.6 Independence Chap. 1: 36, 37, 40, 43, 45, 47
8/8 -

Quiz 1

-
9/8 -

Holiday

3 12/8 -

Holiday

14/8 2.1-2.2 Discrete random variables Chap. 2: 1, 2, 4, 5, 9, 16, 17, 20, 30
15/8 -

Holiday

-
16/8 2.3 Continuous random variables Chap. 2: 33, 34, 35, 36, 38
4 19/8 2.4 Expectation Chap. 2: 39, 40, 41, 47
21/8 2.5 Functions of random variables Chap. 2: 46, 47, 48
22/8 -

Quiz 2

-
23/8 2.5 Functions of random variables
5 26/8 2.5 Joint random variables Chap. 2: 49, 50, 53, 55
28/8 2.5 Independence Chap. 2: 56, 58, 59, 66
29/8 -

Quiz 3

-
30/8 2.5 Covariance Chap 2: 54, 60, 62, 63
6 2/9 -

Holiday

4/9 2.5 Change of variables formulas Chap 2: 68
5/9 -

Quiz 4

-
6/9 2.6 Moment generating functions Chap 2: 67, 69, 70
7 9/9 2.8 Limit theorems Chap 2: 76, 78, 81, 83, 86
11/9 2.9 Stochastic processes none
12/9 -

Quiz 5

-
13/9 3.1-3.2 Conditional probability Chap. 3: 1, 3, 5, 8
8 16/9

Class cancelled

18/9 3.3-3.4 Conditional expectation Chap. 3: 11, 12, 15, 19, 21, 26, 30
19/9 -

Quiz 6

-
20/9 3.4 Conditional Variance formula Chap. 3: 36, 38, 40, 49, 50
9 23/9

No class (midterm week)

25/9

Midsemester exam, 9-11am, LH4

26/9 -

No class (midterm week)

-
27/9

No class (midterm week)

10 30/9 3.5 Probabilities by conditioning Chap. 3: 53, 54, 56, 60
2/10 -

Holiday

3/10 -

Quiz 7

-
4/10 4.1 Introduction to Markov chains Chap. 4: 1, 3, 4, 6
11 7/10 4.2 Chapman-Kolmogorov equation Chap. 4: 9, 12, 13
9/10 4.3 Communication classes Chap. 4: 15, 18(b), 21(a)
10/10 -

Quiz 8

-
11/10 4.3 Recurrence and transience Chap. 4: 14, 16,
12 14/10 4.4 Long run proportions Chap. 4: 20, 21(b), 22, 24
16/10 4.4 Stationary distribution Chap. 4: 25, 26, 27, 28
17/10 -

Quiz 9

-
18/10 4.6 Examples of Markov chains
13 21/10
23/10
24/10 -

Quiz 10

-
25/10
14 28/10
30/10
31/10 -

Quiz 11

-
1/11 -

Holiday

15 4/11
6/11
7/11 -

Quiz 12

-
8/11
16 11/11
13/11
14/11 -

Quiz 13

-
15/11

Class cancelled

16 18/11
20/11
21/11 -

Quiz 14

-
22/11