**Review by**

Tejas Bhalla, 2023(BTech)

**Course Offered In**

Autumn 2020

**Instructors**

Prof. S. Baskar

**Prerequisites**

None.

**Difficulty**

3/5

**Course Content**

The course covers the following topics-

- Concepts of Probability: Probability Space, Conditional Probability
- Random Variables and Distributions: Discrete and Continuous Random Variables, Random Vectors
- Expectations: Definition, Moments
- Limit Theorems: Types of Convergence, Law of Large Numbers

**Feedback on Lectures**

Being a Covid sem, the lectures were uploaded on YouTube to be viewed at any time. The videos primarily consisted of sir going through the notes created, and explaining with examples in some cases. The slots for lectures were reserved for doubt clearing sessions. The notes created by sir were extensive and complete and were alone sufficient for the whole course.

**Feedback on Evaluations**

The only evaluation conducted was 10 quizzes with the midden and endsems being 2 quizzes each. Each quiz was of 10% weightage and were open notes (both personal and sir’s notes). The exams would have 3 questions for 5 marks each and you could attempt all 3. The quizzes were out of 10 marks only and if you solved all 3 questions and scored above 10, it would be truncated to 10 marks directly. This made the exams much easier, but solving all 3 was tough in the time limit.

**Study Material and References**

- Sir’s notes were sufficient
- (https://www.probabilitycourse.com/)

**Follow-up Courses**

The rest of the minor.

**Final Takeaways**

This course is pretty much a copy of EE 325 which it runs parallel with and thus is significantly easier to do, but the mathematical proofs needed can make it tougher at places.

**Grading Statistics:**