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Convolutions
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Classroom Contents
Probability Theory and Applications
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- 1 Queuing Models M/M/I Birth and Death Process Little's Formulae
- 2 Strong law of large numbers, Joint mgf
- 3 Reducible markov chains
- 4 Inter-arrival times, Properties of Poisson processes
- 5 Applications of central limit theorem
- 6 Random walk, periodic and null states
- 7 Poisson processes
- 8 Central limit theorem
- 9 First passage and first return prob. Classification of states
- 10 Convergence and limit theorems
- 11 State prob.First passage and First return prob
- 12 M/M/I/K & M/M/S/K Models
- 13 Inequalities and bounds
- 14 Transition and state probabilities
- 15 M/M/S M/M/I/K Model
- 16 Stochastic processes:Markov process
- 17 Convolutions
- 18 Time Reversible Markov Chains
- 19 Analysis of L,Lq,W and Wq, M/M/S Model
- 20 Reliability of systems
- 21 Exponential Failure law, Weibull Law
- 22 Application to Reliability theory failure law
- 23 Function of Random variables,moment generating function
- 24 Continuous random variables and their distributions
- 25 Continuous random variables and their distributions
- 26 Discreet random variables and their distributions
- 27 Discreet random variables and their distributions
- 28 Discrete random variables and their distributions
