本书根据编者多年的双语教学经验编写，介绍了概率论与数理统计的基本概念、原理、计算方法，以及实际应用。在编写过程中，吸取了国内外优秀教材的优点，注重理论与实践相结合，系统性强，图例丰富，突出统计思想，着力培养学生分析问题和解决实际问题的能力。
本书主要内容包括概率与随机事件、随机变量及其分布、多维随机变量及其分布、随机变量的数字特征、大数定律和中心极限定理、参数估计、假设检验、线性回归分析和统计软件R的介绍。每章中精选了实用性强的例题和习题。
本书可作为高等院校理工科各专业本科生“概率论与数理统计”课程的双语教材，也可供工程技术人员、科技工作者参考。

Chapter 1 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
Exercise 1
Chapter 2 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 Usefu1 Continuous Distributions
2.7 Functions of a Random Variable
Exercise 2
Chapter 3 Multivariate Probability Distributions
3.1 Bivariate Distributions
3.2 Marginal Distributions
3.3 Conditional Distrmutions
3.4 Independent Random Variables
3.5 Functions of Two or More Random Variables
Exercise 3
Chapter 4 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 Covariance Matrix
Exereise 4
Chapter 5 Large Random Samples
5.1 The Law of Large Numbers
5.2 The CentraI Limit Theorem
Exercise 5
Chapter 6 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
Exercise 6
Chapter 7 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
Exercise 7
Chapter 8 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
Exercise 8
Chapter 9 Introduction to R language
9.1 Features of R Language
9.2 R Installation
9.3 Vector, Matrix and Data Frame
9.4 Loop and Branch Control Statements
9.5 Common Probability Distributions
9.6 Some Examples
Appendix A Binomial Probability Distribution
Appendix B Poisson Cmnulative Distribution
Appendix C Standard Normal Table
Appendix D t-distribution Upper Quantiles tα(n)
Appendix E f-distribution Upper QuantilessX2α(n)
Appendix F F-distribution Upper Quantiles R(n1，n2)
Appendix G Some Common Probability Distributions
Bibliography