内容简介

本书采用学生易于接受的知识结构方式和英语表述方式，科学、系统地介绍了概率论与数理统计中随机事件、概率的三个定义、古典概率的计算、条件概率、全概率以及贝叶斯定理、一维随机变量及概率分布、二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、样本及抽样分布、参数估计、假设检验、线性回归、方差分析等知识。本书强调通用性和适用性，兼顾先进性，起点低，难度适中，语言简洁明了，不仅适用于课堂教学使用，同时也适用于自学自习。全书每章有习题配置，题量适中，题型全面，书后附有答案。本书读者对象为高等院校理工、财经、医药、农林等专业大学生和教师，特别适合作为中外合作办学的国际教育班的学生以及准备出国留学深造学生的参考书。

目录

1AxiomsofProbability
1.1Introduction
1.2SampleSpaceandEvents
1.3TheRelativeFrequencyDefinitionofProbability
1.4AxiomsofProbability
1.5SampleSpacesHavingEquallyLikelyOutcomes
1.6ConditionalProbability
1.7TheLawofTotalProbability（PartitionTheorem）
1.8BayesTheoremExercises
2RandomVariablesandTheirDistributions
2.1RandomVariables
2.2DiscreteRandomVariables
2.3SomeImportantDiscreteProbabilityDistributions
2.4CumulativeDistributionFunctions
2.5ContinuousRandomVariables
2.6SomeImportantContinuousProbabilityDistributions
2.7DistributionsofFunctionsofaRandomVariableExercises
3MultivariateRandomVariables
3.1JointDistributionFunction
3.2IndependentRandomVariables
3.3ConditionalDistributions
3.4TwoParticularMultivariateDistribution
3.5DistributionsofSpecialFunctionsofTwoRandomVariables
4TheExpectationandVariance
4.1ExpectationsofRandomVariables
4.2TheVarianceofRandomVariables
4.3SomeImportantExpectationsandVariance
4.4CovarianceandCorrelation
5TheLawofLargeNumbersandtheCentralLimitTheorem
5.1ChebyshevsInequality
5.2LawofLargeNumbers
5.3TheCentralLimitTheoremExercisesPartBStatisticalInference
6SamplingDistributionsofEstimators
6.1RandomSampling
6.2SomeImportantStatistics
6.3SamplingDistributions
7ParameterEstimation
7.1PointEstimation
7.2TheParticularPropertiesofEstimators
7.3IntervalEstimation
8HypothesisTesting
8.1Introduction
8.2TestsConcerningMean
8.3TestsConcerningVariance
8.4p-ValuesExercises