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Introduction to probability: statistics and random processes / Hossein Pishro-Nik

By: Pishro-Nik, Hossein [author]Material type: Text

TextPublication details: [Blue Bell, PA] : Kappa Research, LLC, 2014Description: ix, 732 pages : illustrations ; 25 cmISBN: 9780990637202Subject(s): PROBABILITIES | STATISTICS | STOCHASTIC PROCESSESLOC classification: QA 273 .P57 2014

Contents:

Basic concepts -- combinatorics: counting methods -- discrete random variables -- continuous and mixed random variables -- joint distributions: two random variables.

Summary: The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.

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Item type	Current library	Home library	Collection	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	LRC - Main	National University - Manila	Electronics and Communications Engineering	General Circulation	GC QA 273 .P57 2014 (Browse shelf (Opens below))	c.1	Available		NULIB000013583

Includes bibliographical references (pages 731-732) and index.

Basic concepts -- combinatorics: counting methods -- discrete random variables -- continuous and mixed random variables -- joint distributions: two random variables.

The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.

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