機率論與數理統計（英文版）

《機率論與數理統計（英文版）》是2018年9月清華大學出版社出版的圖書，作者是桂文豪。

基本介紹

• 中文名：機率論與數理統計（英文版）
• 作者：桂文豪
• 出版社：清華大學出版社
• 出版時間：2018年9月
• 定價：42 元
• ISBN：9787512136526

內容簡介

本書根據編者多年的雙語教學經驗編寫,介紹了機率論與數理統計的基本概念、原理、計算方法,以及實際套用.在編寫過程中,吸取了國內外優秀教材的優點,注重理論與實踐相結合,系統性強,圖例豐富,突出統計思想,著力培養學生分析問題和解決實際問題的能力.

本書主要內容包括機率與隨機事件、隨機變數及其分布、多維隨機變數及其分布、隨機變數的數字特徵、大數定律和中心極限定理、參數估計、假設檢驗、線性回歸分析.每章中精選了的實用性強的例題和習題.

本書可作為高等院校理工科各專業本科生的機率論與數理統計課程雙語教材,也可供工程技術人員、科技工作者參考。

圖書目錄

Chapter1　Introduction to Probability

1．1　Random Experiments

1．2　Sample Space

1．3　Relations and Operations between Events

1．4　The Definition of Probability

1．5　Equally Likely Outcomes Model

1．6　Conditional Probability

1．7　Total Probability and Bayes' Theorem

1．8　Independent Events

Exercise1

Chapter2　Random Variables and Distributions

2．1　Random Variables

2．2　Cumulative Distribution Function

2．3　Discrete Distributions

2．4　Some Common Discrete Distributions

2．5　Continuous Distributions

2．6　Some Useful Continuous Distributions

2．7　Functions of a Random Variable

Exercise2

Chapter3　Multivariate Probability Distributions

3．1　Bivariate Distributions

3．2　Marginal Distributions

3．3　Conditional Distributions

3．4　Independent Random Variables

3．5　Functions of TwoorMoreRandom Variables

Exercise3

Chapter4　Characteristics of Random Variables

4．1　The Expectation of a Random Variable

4．2　Variance

4．3　The Characteristics of some Common Distributions

4．4　Chebyshev's Inequality

4．5　Covariance and Correlation Coefficient

4．6　Moment and CovarianceMatrix

Exercise4

Chapter5　Large Random Samples

5．1　The Law of Large Numbers

5．2　The Central Limit Theorem

Exercise5

Chapter6　Estimation

6．1　Population and Sample

6．2　Moment Estimation

6．3　Maximum Likelihood Estimation

6．4　Properties of Estimators

6．5　Three Important Distributions

6．6　Confidence Intervals

Exercise6

Chapter7　Hypothesis Testing

7．1　Basics of Hypothesis Testing

7．2　Hypothesis Tests for a Population Mean

7．3　Testing Differences between Means

7．4　Hypothesis Tests for One or Two Variances

7．5　Goodness of Fit Tests

Exercise7

Chapter8　Linear Regression

8．1　Linear Regression Model

8．2　Least Squares Estimation

8．3　Properties of Linear Regression Estimators

8．4　Inferences Concerning the Slope

8．5　Regression Validity

8．6　Confidence Interval for Mean Response

8．7　Inference for Prediction

Exercise8

Appendix A　Binomial Probability Distribution

Appendix B　Poisson Cumulative Distribution

Appendix C　Standard Normal Table

Appendix D　t-distribution Upper Quantiles tα(n)

Appendix E　χ2-distribution Upper Quantiles χ2α(n)

Appendix F　F-distribution Upper Quantiles Fα(n1,n2)

Appendix G　Some Common Probability Distributions

Bibliography