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Introduction to Probability, Statistics, and Random Processes

University of Massachusetts Amherst via Independent

Description

This site is the homepage of the textbook Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik. It is an open access peer-reviewed textbook intended for undergraduate as well as first-year graduate level courses on the subject. It can be used by both students and practitioners in engineering, mathematics, finance, and other related fields.

The site includes:

  • The entire textbook
  • Short video lectures that aid in learning the material
  • Online calculators for important functions and distributions
  • A solutions manual for instructors

 NOTE: Videos are only availaible for chapter 1-4

Tags
Cybersecurity Fitness

Syllabus

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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Introduction to Probability, Statistics, and Random Processes

University of Massachusetts Amherst
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    Online Courses
  • Provider
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This site is the homepage of the textbook Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik. It is an open access peer-reviewed textbook intended for undergraduate as well as first-year graduate level courses on the subject. It can be used by both students and practitioners in engineering, mathematics, finance, and other related fields.

The site includes:

  • The entire textbook
  • Short video lectures that aid in learning the material
  • Online calculators for important functions and distributions
  • A solutions manual for instructors

 NOTE: Videos are only availaible for chapter 1-4

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

 

Tags

Cybersecurity Fitness

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