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

By: Material type: TextTextPublication details: [Blue Bell, PA] : Kappa Research, LLC, c2014Description: ix, 732 pages : illustrations ; 25 cmISBN:
  • 9780990637202
Subject(s): LOC 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.
Item type: Books
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Holdings
Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Main General Circulation Electronics and Communications Engineering 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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