Book , Print in English

A first course in probability

Sheldon Ross, University of Southern California.
  • Boston : Pearson, [2014]
  • Ninth edition.
  • xi, 457 pages : illustrations ; 26 cm
Subjects
Genre
  • Textbooks.
Contents
  • note: 1.1. Introduction
  • 1.2. Basic Principle of Counting
  • 1.3. Permutations
  • 1.4. Combinations
  • 1.5. Multinomial Coefficients
  • 1.6. Number of Integer Solutions of Equations
  • 2.1. Introduction
  • 2.2. Sample Space and Events
  • 2.3. Axioms of Probability
  • 2.4. Some Simple Propositions
  • 2.5. Sample Spaces Having Equally Likely Outcomes
  • 2.6. Probability as a Continuous Set Function
  • 2.7. Probability as a Measure of Belief
  • 3.1. Introduction
  • 3.2. Conditional Probabilities
  • 3.3. Bayes's Formula
  • 3.4. Independent Events
  • 3.5. P(·|F) Is a Probability
  • 4.1. Random Variables
  • 4.2. Discrete Random Variables
  • 4.3. Expected Value
  • 4.4. Expectation of a Function of a Random Variable
  • 4.5. Variance
  • 4.6. Bernoulli and Binomial Random Variables
  • 4.7. Poisson Random Variable
  • 4.8. Other Discrete Probability Distributions
  • 4.9. Expected Value of Sums of Random Variables
  • 4.10. Properties of the Cumulative Distribution Function
  • 5.1. Introduction
  • 5.2. Expectation and Variance of Continuous Random Variables
  • 5.3. Uniform Random Variable
  • 5.4. Normal Random Variables
  • 5.5. Exponential Random Variables
  • 5.6. Other Continuous Distributions
  • 5.7. Distribution of a Function of a Random Variable
  • 6.1. Joint Distribution Functions
  • 6.2. Independent Random Variables
  • 6.3. Sums of Independent Random Variables
  • 6.4. Conditional Distributions: Discrete Case
  • 6.5. Conditional Distributions: Continuous Case
  • 6.6. Order Statistics
  • 6.7. Joint Probability Distribution of Functions of Random Variables
  • 6.8. Exchangeable Random Variables
  • 7.1. Introduction
  • 7.2. Expectation of Sums of Random Variables
  • 7.3. Moments of the Number of Events that Occur
  • 7.4. Covariance, Variance of Sums, and Correlations
  • 7.5. Conditional Expectation
  • 7.6. Conditional Expectation and Prediction
  • 7.7. Moment Generating Functions
  • 7.8. Additional Properties of Normal Random Variables
  • 7.9. General Definition of Expectation
  • 8.1. Introduction
  • 8.2. Chebyshev's Inequality and the Weak Law of Large Numbers
  • 8.3. Central Limit Theorem
  • 8.4. Strong Law of Large Numbers
  • 8.5. Other Inequalities
  • 8.6. Bounding the Error Probability When Approximating a Sum of Independent Bernoulli Random Variables by a Poisson Random Variable
  • 9.1. Poisson Process
  • 9.2. Markov Chains
  • 9.3. Surprise, Uncertainty, and Entropy
  • 9.4. Coding Theory and Entropy
  • 10.1. Introduction
  • 10.2. General Techniques for Simulating Continuous Random Variables
  • 10.3. Simulating from Discrete Distributions
  • 10.4. Variance Reduction Techniques.
Other information
  • Includes bibliographical references and index.
ISBN
  • 9780321794772
  • 032179477X
  • 9789332519077
  • 9332519072
Identifying numbers
  • LCCN: 2012023212
  • OCLC: 803961222
  • OCLC: 803961222