[内容简介]

《华 章统计学原版精品系列：概率与统计（英文版）》中的统计方法大多是现代统计学的常用统计理论与方法，在介绍每一种统计方法前都详细叙述统计方法的思想。注 重实际应用。把抽象的统计理论与方法进行直观描述与总结，不偏重理论的推导，而是注重具体应用。内容丰富，实用性强。书中含有大量的例子和习题，通过真 实、科学的模型方案和数据使读者掌握统计方法。这些例子和习题不局限于工程领域，还包括一些社会学、经济学、生物学、物理学和计算机科学领域的应用。要求 数学知识少。只要读者掌握基本的微积分和非常简单的矩阵运算知识，就可以畅通无阻地阅读全书，并能应用所介绍的统计方法。

[目录]

Preface
1  IntrOduCtiONtoStatisticsandProbability
1.1  Overview：StatisticalInference，Samples，Populations，andthe
RoleofProbability
l.2  SamplingProcedures；CollectionofData
l.3  DiscreteandContinuousData
1.4  Probability：SampleSpaceandEvents
Exercises
1.5  CountingSamplePoints
Exercises
1.6  ProbabilityofanEvent
1.7  AdditiveRules
Exercises
1.8  ConditionalProbability，Independence，andtheProductRule
EXercises
1.9  Bayes’Rule
EXercises
RevJewExercises
2  RandomVariables，Distributions
andExpectations
2.1  ConceptofaRandomVariable
2.2  DiscretcProbabilityDistributions
2.3  ContinuousProbabilityDistributions
EXCrCiscS
2.4  JointProbabilityDistributions
EXcrCiscS
2.5  McanofaRandomVariable
EXcrciscs
2.6  VarineeandCovarianceofRandomVariablessl
Exercisess
2.7  MesnsandVariancesofI，inem&"Combin~tionsofRandomVariables
Exercises
ReviewExerdses
2sPotentiaLMisconceptionsandHazards
RelationshiptoMa~erialinOtherChapters
3  SomeProbabilityDistributions
3.1  IntroductionandMotivation
3.2  BinomialandMultinomialDistributions
Exercises
3.3  HypergeometricDistribution
Exercises
3.4  NegativeBinomialandGeometricDistributions
n5PoissonDistributionandthePoissonProcess
Exercises
3.6  ContinuousUniformDistribution
3.7  NonnalDistribution
3.8  sAteasundertheNormalCurve
3.9  ApplicationsoftheNormalDistrihution
Exercises
31.0NormalApproximationtotheBinomial
Exercises
3.11  GaromaandExponentialDistrlbutlons
3.12  Chi-SquaredDistribution
Exercises
ReviewExercises
313PotelitialMisconceptionsandHazardsRelationshiptoMaterialinOtherChapters
4  SamplingDistributionsandDataDescriptions
4.1  RandomSampling
4.2  SomeImportantStatisticsExercises
4.3  SamplingDistributions
4.4  SamplingDistributionOFeansandtheCentralLimitTheoremExercises
4.5  SamplingDistributionofS