NOC:Probability and Random Processes

Lecture 1 - Introduction

Lecture 2 - Algebra of Events

Lecture 3 - Axioms of Probability

Lecture 4 - Example 1

Lecture 5 - Example 2

Lecture 6 - Example 3

Lecture 7 - Example 4

Lecture 8 - Example 5

Lecture 9 - Conditional Probability

Lecture 10 - Bayes Theorem 1

Lecture 11 - Bayes Theorem 2

Lecture 12 - A Brief Review

Lecture 13 - Example 1

Lecture 14 - Example 2

Lecture 15 - Example 3

Lecture 16 - Example 4

Lecture 17 - Example 5

Lecture 18 - Independent Events

Lecture 19 - A Brief Review

Lecture 20 - Example 1

Lecture 21 - Example 2

Lecture 22 - Example 3

Lecture 23 - Example 4

Lecture 24 - Discrete Random Variables

Lecture 25 - Expectation

Lecture 26 - Moments

Lecture 27 - Variance

Lecture 28 - Binomial Random Variables

Lecture 29 - Poisson Random Variables

Lecture 30 - More on Poission Random Variables

Lecture 31 - Properties of the CDF

Lecture 32 - A Brief Review - I

Lecture 33 - A Brief Review - II

Lecture 34 - Example 1

Lecture 35 - Example 2

Lecture 36 - Example 3

Lecture 37 - Example 4

Lecture 38 - Example 5

Lecture 39 - Example 6

Lecture 40 - Example 7

Lecture 41 - Example 8

Lecture 42 - Example 9

Lecture 43 - Continuous Random Variables

Lecture 44 - Expectation of Continuous random variables

Lecture 45 - The uniform and the Gaussian Random variables

Lecture 46 - The mean and variance of a Gaussian Random Variable

Lecture 47 - The exponential random variable and other continuous distributions

Lecture 48 - A Brief Review

Lecture 49 - Example 1

Lecture 50 - Example 2

Lecture 51 - Example 3

Lecture 52 - Example 4

Lecture 53 - Example 5

Lecture 54 - Functions of a random varible

Lecture 55 - Functions of a random varible

Lecture 56 - The moment generating function

Lecture 57 - Conditional Distributions

Lecture 58 - Bivariate Distributions

Lecture 59 - Independence of Random Varibles

Lecture 60 - Jointly Gaussian Random Varibales and Circular symmetry

Lecture 61 - Jointly Discrete Random Variables

Lecture 62 - One Function of two random variables

Lecture 63 - Order Statistics

Lecture 64 - Two functions of two random variables

Lecture 65 - Joint Moments

Lecture 66 - Joint Charactristic Functions

Lecture 67 - Conditional Distributions for multiple random variables

Lecture 68 - Conditional Expectations

Lecture 69 - Examples

Lecture 70 - Random Vectors

Lecture 71 - Independence of Random Varibles

Lecture 72 - Complex Random Varibales

Lecture 73 - Covariance Matrices

Lecture 74 - Conditional Densities

Lecture 75 - Gaussianity

Lecture 76 - Chi Squared Densities

Lecture 77 - Examples

Lecture 78 - Estimation Theory

Lecture 79 - Measurements

Lecture 80 - Sequences of Random Variables

Lecture 81 - Laws of large numbers

Lecture 82 - Random processes

Lecture 83 - Stationarity, Cyclostationarity, Ergodicity

Lecture 84 - Random Processes as Signals (PSD and LTI Response)

Lecture 85 - White and Gaussian Processes Noise