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Lec 33 Some Problems

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Lesson extensions

Lessons List | 35 Lesson

Discrete time Markov Chains and Poisson Processes Intro Video

Discrete time Markov Chains and Poisson Processes Intro Video

Lec 1 Review of Basic Probability I

Lec 1 Review of Basic Probability I

Lec 2 Review of Basic Probability II

Lec 2 Review of Basic Probability II

Lec 3 Review of Basic Probability III

Lec 3 Review of Basic Probability III

Lec 4 Stochastic Processes

Lec 4 Stochastic Processes

Lec 5 Definition of Markov Chain and Transition Probabilities

Lec 5 Definition of Markov Chain and Transition Probabilities

Lec 6 Markov Property and Chapman Kolmogorov Equations

Lec 6 Markov Property and Chapman Kolmogorov Equations

Lec 7 Chapman Kolmogorov Equations Examples

Lec 7 Chapman Kolmogorov Equations Examples

Lec 8 Accessibility and Communication of States

Lec 8 Accessibility and Communication of States

Lec 9 Hitting Time I

Lec 9 Hitting Time I

Lec 10 Hitting Time II

Lec 10 Hitting Time II

Lec 11 Hitting Time III

Lec 11 Hitting Time III

Lec 12 Strong Markov Property

Lec 12 Strong Markov Property

Lec 13 Passage Time and Excursion

Lec 13 Passage Time and Excursion

Lec 14 Number of Visits

Lec 14 Number of Visits

Lec 15 Class Property

Lec 15 Class Property

Lec 16 Transience and Recurrence of Random Walks

Lec 16 Transience and Recurrence of Random Walks

Lec 17 Stationary Distribution I

Lec 17 Stationary Distribution I

Lec 18 Stationary Distribution II

Lec 18 Stationary Distribution II

Lec 19 Stationary Distribution III

Lec 19 Stationary Distribution III

Lec 20 Limit Theorems I

Lec 20 Limit Theorems I

Lec 21 Limit Theorems II

Lec 21 Limit Theorems II

Lec 22 Some Problems I

Lec 22 Some Problems I

Lec 23 Some Problems II

Lec 23 Some Problems II

Lec 24 Time Reversibility

Lec 24 Time Reversibility

Lec 25 Properties of Exponential Distribution

Lec 25 Properties of Exponential Distribution

Lec 26 Some Problems

Lec 26 Some Problems

Lec 27 Order Statistics

Lec 27 Order Statistics

Lec 28 Poisson Processes

Lec 28 Poisson Processes

Lec 29 Poisson Thinning I

Lec 29 Poisson Thinning I

Lec 30 Poisson Thinning II

Lec 30 Poisson Thinning II

Lec 31 Conditional Arrival Times

Lec 31 Conditional Arrival Times

Lec 32 Independent Poisson Processes

Lec 32 Independent Poisson Processes

Lec 33 Some Problems

Lec 33 Some Problems

Lec 34 Compound Poisson Processes

Lec 34 Compound Poisson Processes

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Course Description

Stationary Distribution course, In this course you'll delve into the fundamentals and practical aspects of Stationary Distribution.

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