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
Related Links
-
Libraries Service CenterChecked outChecked out, Due: Jun 18 2021Another patron is currently using this item. Use BorrowDirect to request a different copy. For additional help, ask a library staff member.
-
Eisenhower C LevelAvailable
-
Washington LRC ReservesAvailable
- 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
