INDIAN MARITIME UNIVERSITY KOLKATA CAMPUS-LIBRARY

Probability & Statistics - Video Lectures

Lec 1 Probability Models and Axioms

Lec 2 Conditioning and Bayes' Rule

Lec 3 Independence

Lec 4 Counting

Lec 5 Discrete Random Variables I

Lec 6 Discrete Random Variables II

Lec 7 Discrete Random Variables III

Lec 8 Continuous Random Variables

Lec 9 Multiple Continuous Random Variables

Lec 10 Continuous Bayes' Rule; Derived Distributions

Lec 11 Derived Distributions (ctd.); Covariance

Lec 12 Iterated Expectations

Lec 13 Bernoulli Process

Lec 14 Poisson Process I

Lec 16 Markov Chains I

Lec 17 Markov Chains II

Lec 18 Markov Chains III

Lec 19 Weak Law of Large Numbers

Lec 20 Central Limit Theorem

Lec 21 Bayesian Statistical Inference I

Lec 23 Bayesian Statistical Inference II

Lec 23 Classical Statistical Inference I

Lec 24 Classical Inference II

Lec 25 Classical Inference III

Lec15 Poisson Process II

Basic Probability

Binomial Distribution 1

Binomial Distribution 2

Binomial Distribution 3

Binomial Distribution 4

Birthday Probability Problem-9

Combinations

Compound Probability of Independent Events

Conditional Probability and Combinations

Dependent Probability Example 1

Dependent Probability Example 2-7

Exactly Three Heads in Five Flips

Expected Value of Binomial Distribution

Expected Value

Frequency Probability and Unfair Coins

Frequency Stability

Generalizing with Binomial Coefficients (bit advanced)

Getting At Least One Heads

Getting Exactly Two Heads (Combinatorics)

Introduction to Random Variables

Law of Large Numbers

LeBron asks about the chances of making 10 free throws

Permutations

Poisson Process 1-3

Poisson Process 2

Probability (part 2)

Probability (part 3)