6.262 Discrete Stochastic Processes (Spring 2011, MIT OCW). Instructor: Professor Robert Gallager. Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals.
FREE
This course includes
Hours of videos
694 years, 4 months
Units & Quizzes
25
Unlimited Lifetime access
Access on mobile app
Certificate of Completion
This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance. (from ocw.mit.edu)
Course Currilcum
- Lecture 01 – Introduction and Probability Review Unlimited
- Lecture 02 – More Review; The Bernoulli Process Unlimited
- Lecture 03 – Law of Large Numbers, Convergence Unlimited
- Lecture 04 – Poisson (the Perfect Arrival Process) Unlimited
- Lecture 05 – Poisson Combining and Splitting Unlimited
- Lecture 06 – From Poisson to Markov Unlimited
- Lecture 07 – Finite-state Markov Chains; The Matrix Approach Unlimited
- Lecture 08 – Markov Eigenvalues and Eigenvectors Unlimited
- Lecture 09 – Markov Rewards and Dynamic Programming Unlimited
- Lecture 10 – Renewals and the Strong Law of Large Numbers Unlimited
- Lecture 11 – Renewals: Strong Law and Rewards Unlimited
- Lecture 12 – Renewal Rewards, Stopping Trials, and Wald’s Inequality Unlimited
- Lecture 13 – Little, M/G/1, Ensemble Averages Unlimited
- Lecture 14 – Review Unlimited
- Lecture 15 – The Last Renewal Unlimited
- Lecture 16 – Renewals and Countable-state Markov Unlimited
- Lecture 17 – Countable-state Markov Chains Unlimited
- Lecture 18 – Countable-state Markov Chains and Processes Unlimited
- Lecture 19 – Countable-state Markov Processes Unlimited
- Lecture 20 – Markov Processes and Random Walks Unlimited
- Lecture 21 – Hypothesis Testing and Random Walks Unlimited
- Lecture 22 – Random Walks and Thresholds Unlimited
- Lecture 23 – Martingales (Plain, Sub, and Super) Unlimited
- Lecture 24 – Martingales: Stopping and Converging Unlimited
- Lecture 25 – Putting It All Together Unlimited
