# IE502: Probabilistic Models

#### Instructor

K.S. Mallikarjuna Rao

#### Section

A single batch. Slot12 (Mon, Thu - 5:30 to 7:00)

#### Semester

Spring’19

#### Course Difficulty

Course started with very basic probability and then covered basic 11th -12th standard probability. The courses ended with the Markov chain. So, the difficulty level increased with the classes but the overall difficulty level was intermediate.

#### Time Commitment Required

A majority part of the course was already taught to us in the 11th-12th standard so the time commitment was relatively less. As new topics were covered, we felt the need to solve practice problems on the topics covered. So other than the classes, 1-2hr a week was more sufficient for the course.

#### Grading

Grading was chill. But only 4 AAs were given out of around 100 students. AB was given to a lot of students (around 30 students got AB).

#### Attendence Policy

Prof asked to mark attendance on SAFE App but did not give any DX grade. However, you should attend all the classes.

#### Pre-requisites

No pre-requisites for this course. If you still remember the probability learned during JEE days then that will really help you.

#### Evaluation Scheme and Weightages

Scheme decided in the first class was-

- 3 Quizzes - 30% (best 2 out of 3)
- 1 Midsem - 30%
- 1 endsem - 40%

#### Topics Covered in the Course

- Probability, Conditioning, and Independence
- Random Variables, Limit Theorems, Random Walks
- Markov chains, Martingales, Poisson processes, Renewal processes, Queuing and Reliability and Applications

#### Mechanism of Instruction and Teaching Style

Most of the classes were covered on the board without any slides. Professor writes and explains everything. For some topics, slides were used. You should try to listen carefully and take notes during the lectures. Some examples taken up are very interesting however class gets boring during the theoretical part (definitions, etc).

#### Assignments and projects in the Course

Assignments/practice problems given we relatively easy for the initial topics and became moderately difficult gradually. Assignments did not carry any weightage.No projects for this course

#### Exams

Very easy quiz and midsem, Endsem were moderate in difficulty level.

#### Reference Material

- Dimitri P. Bertsekas and John N. Tsitsiklis, Introduction to Probability, Athena Scientific.
- Kai L. Chung, A Course in Probability Theory, Academic Press.
- William Feller, An Introduction to Probability Theory and Its Applications (2 Vols), Wiley.
- Charles M. Grinstead and J. L. Snell, Introduction to Probability, AMS.
- Jim Pitman, Probability, Springer.
- Jean Jacod and Philip Protter, Probability Essentials, Springer.
- Sheldon Ross, Probability Models, Academic Press.
- Santosh S. Venkatesh, The Theory of Probability, Cambrdige University Press.

#### Importance of Course

Can be tagged as Department Elective This course might be helpful for students pursuing CS minor since it covers a bit of queuing theory. A course on probability also looks good in terms of interview for internship/placement for analytics/coding profile. Sometimes, questions on probability are asked in the interviews so this course might help

#### Anything else relevant to the course

Prof took a lot of leaves. So took extra lectures on 1-2 Saturdays