### Module 1 – introduction to probability

Lecture 1 – Classical definition of probability

Lecture 2 – Theorems in probability

Lecture 3 – Problems in probability

Lecture 4 – Conditional probability

Lecture 6 – Problems based on Bayers theorem

**Module 2 – Random variable**

Lecture 7 – Random variable & Probability distribution

Lecture 10 – Change of variable

### Module 3- Mathematical expectation

Lecture 11 – Mathematical expectation PART 1

Lecture 12 – Mathematical expectation PART 2

Lecture 13 – Mathematical expectation PART 3

### Module 4 – Bivariate random variables

Lecture 14 – Joint probability functions

Lecture 15 – Problems in Bivariate RV PART 1

Lecture 16 – Problems in Bivariate rvs PART 2

Lecture 17 – Mathematical expectation for Bivariate data

Lecture 18 – Some results in expectation

Lecture 19 – Conditional expectation & Variance

Lecture 20 – Problems based on conditional mean & variance PART 1

Lecture 21 – Problems based on conditional mean & variance PART 2

Lecture 22 – Problems based on conditional expectation & variance