概率论基础教程(英文版)(第7版)

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基本信息·出版社:人民邮电出版社

·页码:565 页

·出版日期:2007年

·ISBN:7115165416

·条形码:9787115165411

·包装版本:1

·装帧:平装

·开本:0开

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内容简介《概率论基础教程》(英文版•第7版)是全球高校广泛采用的概率论教材,通过大量的例子讲述了概率论的基础知识,主要内容有组合分析概率论公理化、条件概率和独立性、离散和连续型随机变量、随机变量的联合分布、期望的性质、极限定理等.本书附有大量的练习,分为习题、理论习题和自检习题三大类,其中自检习题部分还给出全部解答。

作者简介Sheldon M.Ross,国际知名概率与统计学家,南加州大学工业工程与运筹系系主任。毕业于斯坦福大学统计系,曾在加州大学伯克利分校任教多年。研究领域包括:随机模型、仿真模拟、统计分析、金融数学等。Ross教授著述颇丰,他的多种畅销数学和统计教材均产生了世界性的影响,如Simulation(《统计模拟》)、Introduction to Probability Models(《应用随机过程:概率模型导论》)等(均由人民邮电出版社出版)。

编辑推荐《概率论基础教程》(英文版•第7版)作为概率论的入门书,适用于大专院校数学、统计、工程和相关专业(包括计算科学、生物、社会科学和管理科学)的学生阅读,也可供概率应用工作者参考。

目录

1Combinatorial Analysis

1.1Introduction

1.2The Basic Principle of Counting

1.3Permutations

1.4Combinations

1.5Multinomial Coefficients

1.6The Number of Integer Solutions of Equations*

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

2Axioms of Probability

2.1Introduction

2.2Sample Space and Events

2.3Axioms of Probability

2.4Some Simple Propositions

2.5Sample Spaces Having Equally Likely Outcomes

2.6Probability as a Continuous Set Function*

2.7Probability as a Measure of Belief

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

3Conditional Probability and Independence

3.1Introduction

3.2Conditional Probabilities

3.3Bayes' Formula

3.4Independent Events

3.5P(.|F) Is a Probability

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

4Random Variables

4.1Random Variables

4.2Discrete Random Variables

4.3Expected Value

4.4Expectation of a Function of a Random Variable

4.5Variance

4.6The Bernoulli and Binomial Random Variables

4.6.1Properties of Binomial Random Variables

4.6.2Computing the Binomial Distribution Function

4.7 ThePoisson Random Variable

4.7.1Computing the Poisson Distribution Function

4.8Other Discrete Probability Distributions

4.8.1The Geometric Random Variable

4.8.2The Negative Binomial Random Variable

4.8.3The Hypergeometric Random Variable

4.8.4The Zeta (or Zipf) Distribution

4.9Properties of the Cumulative Distribution Function

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

5Continuous Random Variables

5.1Introduction

5.2Expectation and Variance of Continuous Random Variables

5.3The Uniform Random Variable

5.4Normal Random Variables

5.4.1The Normal Approximation to the Binomial Distribution

5.5Exponential Random Variables

5.5.1Hazard Rate Functions

5.6Other Continuous Distributions

5.6.1The Gamma Distribution

5.6.2The Weibull Distribution

5.6.3The Cauchy Distribution

5.6.4The Beta Distribution

5.7The Distribution of a Function of a Random Variable

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

6Jointly Distributed Random Variables

6.1Joint Distribution Functions

6.2Independent Random Variables

6.3Sums of Independent Random Variables

6.4Conditional Distributions: Discrete Case

6.5Conditional Distributions: Continuous Case

6.6Order Statistics*

6.7Joint Probability Distribution of Functions of Random Variables

6.8Exchangeable Random Variables*

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

7Properties of Expectation

7.1Introduction

7.2Expectation of Sums of Random Variables

7.2.1Obtaining Bounds from Expectations via the Probabilistic Method*

7.2.2The Maximum-Minimums Identity*

7.3Moments of the Number of Events that Occur

7.4Covariance, Variance of Sums, and Correlations

7.5Conditional Expectation

7.5.1Definitions

7.5.2Computing Expectations by Conditioning

7.5.3Computing Probabilities by Conditioning

7.5.4Conditional Variance

7.6Conditional Expectation and Prediction

7.7Moment Generating Functions

7.7.1Joint Moment Generating Functions

7.8Additional Properties of Normal Random Variables

7.8.1The Multivariate Normal Distribution

7.8.2The Joint Distribution of the Sample Mean and Sample Variance

7.9General Definition of Expectation

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

8Limit Theorems

8.1Introduction

8.2Chebyshev's Inequality and the Weak Law of Large Numbers

8.3The Central Limit Theorem

8.4The Strong Law of Large Numbers

8.5Other Inequalities

8.6Bounding The Error Probability

Summary

Problems

Theoretical Exercises

Self-Test Problems and Exercises

9Additional Topics in Probability

9.1The Poisson Process

9.2Markov Chains

9.3Surprise, Uncertainty, and Entropy

9.4Coding Theory and Entropy

Summary

Theoretical Exercises

Self-Test Problems and Exercises

10Simulation

10.1Introduction

10.2General Techniques for Simulating Continuous Random Variables

10.2.1The Inverse Transformation Method

10.2.2The Rejection Method

10.3Simulating from Discrete Distributions

10.4Variance Reduction Techniques

10.4.1Use of Antithetic Variables

10.4.2Variance Reduction by Conditioning

10.4.3Control Variates

Summary

Problems

Self-Test Problems and Exercises

APPENDICES

AAnswers to Selected Problems

BSolutions to Self-Test Problems and Exercises

Index

……[看更多目录]

 
 
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