Probability Theory and Applications
Offered By: NIOS via YouTube
Course Description
Overview
Syllabus
Queuing Models M/M/I Birth and Death Process Little's Formulae.
Strong law of large numbers, Joint mgf.
Reducible markov chains.
Inter-arrival times, Properties of Poisson processes.
Applications of central limit theorem.
Random walk, periodic and null states.
Poisson processes.
Central limit theorem.
First passage and first return prob. Classification of states.
Convergence and limit theorems.
State prob.First passage and First return prob.
M/M/I/K & M/M/S/K Models.
Inequalities and bounds.
Transition and state probabilities.
M/M/S M/M/I/K Model.
Stochastic processes:Markov process.
Convolutions.
Time Reversible Markov Chains.
Analysis of L,Lq,W and Wq, M/M/S Model.
Reliability of systems.
Exponential Failure law, Weibull Law.
Application to Reliability theory failure law.
Function of Random variables,moment generating function.
Continuous random variables and their distributions.
Continuous random variables and their distributions.
Discreet random variables and their distributions.
Discreet random variables and their distributions.
Discrete random variables and their distributions.
Taught by
Ch 30 NIOS: Gyanamrit
Related Courses
Probability - The Science of Uncertainty and DataMassachusetts Institute of Technology via edX Introduction to Probability, Statistics, and Random Processes
University of Massachusetts Amherst via Independent Queuing Theory: from Markov Chains to Multi-Server Systems
Institut Mines-Télécom via edX Stochastic processes
Higher School of Economics via Coursera Introduction to Stochastic Processes
Indian Institute of Technology Bombay via Swayam