《機率論基礎教程 （英文版） （第8版）》是機械工業出版社出版的圖書，作者是Sheldon Ross。
基本介紹
- 中文名：機率論基礎教程 （英文版） （第8版）
- 作者：Sheldon Ross
- 出版時間：2014年11月1日
- 出版社：機械工業出版社
- 頁數：465 頁
- ISBN：9787111482772
- 裝幀：平裝
內容簡介,圖書目錄,作者簡介,
內容簡介
機率論是研究自然界和人類社會中*現象數量規律的數學分支，本書通過大量的例子講述了機率論的基礎知識，主要內容有組合分析、機率論公理化、條件機率和獨立性、離散和連續型*變數、*變數的聯合分布、期望的性質、極限定理等。本書附有大量的練習，分為習題、理論習題和自檢習題三大類，其中自檢習題部分還給出全部解答。本書作為機率論的入門書，適用於大專院校數學、統計、工程和相關專業(包括計算科學、生物、社會科學和管理科學)的學生閱讀，也可供套用工作者參考。
圖書目錄
COMBINATORIAL ANALYSIS
1.1 Introduction
1.2 The Basic Principle of Counting
1.3 Permutations
1.4 Combinations
1.5 Multinomial Coefficients
1.6 The Number of Integer Solutions of Equations
AXIOMS OF PROBABILITY
Introduction
Sample Space and Events
Axioms of Probability
Some Simple Propositions
Sample Spaces Having Equally Likely
Outcomes
Probability as a Continuous Set Function
Probability as a Measure of Belief
CONDITIONAL PROBABILITY
AND INDEPENDENCE
3.1 Introduction
3.2 Conditional Probabilities
3.3 Bayes's Formula
3.4 Independent Events
3.S P(F) Is a Probability
4 RANDOM VARIABLES
4.1 Random Variables it
4.2 Discrete Random Variables
4.3 Expected Value
4.4 Expectation of a Function of a Random
Variable
4.5 Variance
4.6 The Bernoulli and Binomial Random
Variables
4.7 The 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
CONTINUOUS RANDOM
VARIABLES
5.1 Introduction
5.2 Expectation and Variance of Continuous
Random Variables
5.3 The Uniform Random Variable
5.4 Normal Random Variables
5.5 Exponential Random Variables
5.6 Other Continuous Distributions
5.7 The Distribution of a Function
of a Random Variable
JOINTLY DISTRIBUTED RANDOM
VARIABLES
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
PROPERTIES OF EXPECTATION
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.S 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
LIMIT THEOREMS
8.1 Introduction
8.2 Chebyshev's Inequality and the Weak
Law of Large Numbers
8.3 The Central Limit Theorem
8.4 The 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
ADDITIONAL TOPICS
IN PROBABILITY
9.1 The Poisson Process
9.2 Markov Chains
9.3 Surprise, Uncertainty, and Entropy
9.4 Coding Theory and Entropy
SIMULATION
10.1 Introduction
10.2 General Techniques for Simulating
Continuous Random Variables
10.3 Simulating from Discrete Distributions
10.4 Variance Reduction Techniques
Answers to Selected Problems
Solutions to Self-Test Problems
and Exercises
Index
作者簡介
作者：（美國）羅斯（Sheldon M.Ross） 羅斯（Sheldon M.Ross）世界著名的套用機率專家和統計學家，現為南加州大學工業與系統工程系Epstei”講座教授。他於1968年在史丹福大學獲得統計學博士學位，在1976年至2004年期間於加州大學伯克利分校任教—其研究領域包括統計模擬、金融工程、套用機率模型、隨機動態規劃等。Ross教授創辦了《Probability in the Enginearing and Informational Sciences》雜誌並一直擔任主編，他的多種暢銷教材均產生了世界性的影響，其中《統計模擬（第5版）》和《隨機過程（第2版）》等均由機械工業出版社引進出版。
