Book description
The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study.
- Demonstrates concepts with more than 100 illustrations, including 2 dozen new drawings
- Expands readers’ understanding of disruptive statistics in a new chapter (chapter 8)
- Provides new chapter on Introduction to Random Processes with 14 new illustrations and tables explaining key concepts.
- Includes two chapters devoted to the two branches of statistics, namely descriptive statistics (chapter 8) and inferential (or inductive) statistics (chapter 9).
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Acknowledgment
- Preface to the Second Edition
- Preface to First Edition
-
Chapter 1: Basic Probability Concepts
- Abstract
- 1.1 Introduction
- 1.2 Sample Space and Events
- 1.3 Definitions of Probability
- 1.4 Applications of Probability
- 1.5 Elementary Set Theory
- 1.6 Properties of Probability
- 1.7 Conditional Probability
- 1.8 Independent Events
- 1.9 Combined Experiments
- 1.10 Basic Combinatorial Analysis
- 1.11 Reliability Applications
- 1.12 Chapter Summary
- 1.13 Problems
- Chapter 2: Random Variables
- Chapter 3: Moments of Random Variables
-
Chapter 4: Special Probability Distributions
- Abstract
- 4.1 Introduction
- 4.2 The Bernoulli Trial and Bernoulli Distribution
- 4.3 Binomial Distribution
- 4.4 Geometric Distribution
- 4.5 Pascal Distribution
- 4.6 Hypergeometric Distribution
- 4.7 Poisson Distribution
- 4.8 Exponential Distribution
- 4.9 Erlang Distribution
- 4.10 Uniform Distribution
- 4.11 Normal Distribution
- 4.12 The Hazard Function
- 4.13 Truncated Probability Distributions
- 4.14 Chapter Summary
- 4.15 Problems
-
Chapter 5: Multiple Random Variables
- Abstract
- 5.1 Introduction
- 5.2 Joint CDFs of Bivariate Random Variables
- 5.3 Discrete Bivariate Random Variables
- 5.4 Continuous Bivariate Random Variables
- 5.5 Determining Probabilities from a Joint CDF
- 5.6 Conditional Distributions
- 5.7 Covariance and Correlation Coefficient
- 5.8 Multivariate Random Variables
- 5.9 Multinomial Distributions
- 5.10 Chapter Summary
- 5.11 Problems
-
Chapter 6: Functions of Random Variables
- Abstract
- 6.1 Introduction
- 6.2 Functions of One Random Variable
- 6.3 Expectation of a Function of One Random Variable
- 6.4 Sums of Independent Random Variables
- 6.5 Minimum of Two Independent Random Variables
- 6.6 Maximum of Two Independent Random Variables
- 6.7 Comparison of the Interconnection Models
- 6.8 Two Functions of Two Random Variables
- 6.9 Laws of Large Numbers
- 6.10 The Central Limit Theorem
- 6.11 Order Statistics
- 6.12 Chapter Summary
- 6.13 Problems
- Chapter 7: Transform Methods
- Chapter 8: Introduction to Descriptive Statistics
- Chapter 9: Introduction to Inferential Statistics
-
Chapter 10: Introduction to Random Processes
- Abstract
- 10.1 Introduction
- 10.2 Classification of Random Processes
- 10.3 Characterizing a Random Process
- 10.4 Crosscorrelation and Crosscovariance Functions
- 10.5 Stationary Random Processes
- 10.6 Ergodic Random Processes
- 10.7 Power Spectral Density
- 10.8 Discrete-Time Random Processes
- 10.9 Chapter Summary
- 10.10 Problems
- Chapter 11: Linear Systems with Random Inputs
- Chapter 12: Special Random Processes
- Appendix: Table of CDF of the Standard Normal Random Variable
- Bibliography
- Index
Product information
- Title: Fundamentals of Applied Probability and Random Processes, 2nd Edition
- Author(s):
- Release date: June 2014
- Publisher(s): Academic Press
- ISBN: 9780128010358
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