东北大学：某学院应用统计学专业《智能仿真建模技术》课程教学大纲

智能仿真建模技术教学大纲SimulationModelling Subject Syllabus，课程信息SubjectInformation课程编号：开课学期：43100313006Subject IDSemester课程分类：所属课群：专业教育PA专业基础MFCategorySection课程学分：总学时/周：3.556Credit PointsTotal Hours/Weeks理论学时：实验学时：506LECT. HoursEXP. HoursPBL学时：实践学时/周：00PBL HoursPRAC.Hours/Weeks开课学院：东北大学适用专业：应用统计学 ASCollegeStream悉尼智能科技学院课程属性：课程模式：必修Compulsory引进UTSPatternMode胡海娟中方课程协调人成绩记载方式百分制MarksNEU CoordinatorHaijuan HuResult Type先修课程概率论与随机变量RequisitesProbability and random variablesRubinsteinRandKroeseD,Simulation and theMonteCarloMethod英文参考教材3rd Edition, Wiley 2017.ENTextbooksGrimmett G and Stirzaker D, Probability and Random Processes. 3rdEdition,Oxford2001中文参考教材周永道，贺平和宁建辉，随机模拟的方法和应用，高等教育出版社，2021CN Textbooks教学资源：https:/lms.cloudcampus.com.cn/courses/38Resources课程负责人(撰写人)：胡海娟提交日期：单击或点击此处输入日期。Subject DirectorHaijuan HuSubmitted Date胡海娟任课教师(含负责人)：Stephen WoodcockHaijuan HuTaught byStephen Woodcock审核人：批准人：韩鹏史闻博Checked byApproved by批准日期：单击或点击此处输入日期。ApprovedDate1 / 14

1 / 14 智能仿真建模技术 教学大纲 Simulation Modelling Subject Syllabus 一、课程信息 Subject Information 课程编号: Subject ID 3100313006 开课学期: Semester 4 课程分类: Category 专业教育 PA 所属课群: Section 专业基础 MF 课程学分: Credit Points 3.5 总学时/周: Total Hours/Weeks 56 理论学时: LECT. Hours 50 实验学时: EXP. Hours 6 PBL 学时: PBL Hours 0 实践学时/周: PRAC. Hours/Weeks 0 开课学院: College 东北大学 悉尼智能科技学院 适用专业: Stream 应用统计学 AS 课程属性: Pattern 必修 Compulsory 课程模式: Mode 引进 UTS 中方课程协调人: NEU Coordinator 胡海娟 Haijuan Hu 成绩记载方式: Result Type 百分制 Marks 先修课程: Requisites 概率论与随机变量 Probability and random variables 英文参考教材: EN Textbooks Rubinstein R and Kroese D, Simulation and the Monte Carlo Method, 3rd Edition, Wiley 2017. Grimmett G and Stirzaker D, Probability and Random Processes. 3rd Edition, Oxford 2001. 中文参考教材: CN Textbooks 周永道，贺平和宁建辉，随机模拟的方法和应用，高等教育出版社， 2021 教学资源: Resources https://lms.cloudcampus.com.cn/courses/38 课程负责人(撰写人): Subject Director 胡海娟 Haijuan Hu 提交日期: Submitted Date 单击或点击此处输 入日期。 任课教师(含负责人): Taught by 胡海娟 Stephen Woodcock Haijuan Hu Stephen Woodcock 审核人: Checked by 韩鹏 批准人: Approved by 史闻博 批准日期: Approved Date 单击或点击此处输 入日期

二、教学目标SubjectLearningObjectives(SLOs)注：毕业要求及指标点可参照悉尼学院本科生培养方案，可根据实际情况增减行数Note: GA and index can be referred from undergraduate program in SSTC website. Please add/reduce lines based on subject《智能仿真建模技术》是应用统计学专业重要的专业基础课程之一。本课程包括随机变量的生成、并用于模拟随机过程，包括泊松过程、随机游走和排队系统、计算数值积分。所考虑的模拟方法包括接受-拒绝、重要性抽样、蒙特卡罗和Metropolis-Hastings算法。此外还介绍统计中的三大分布，参数估计，广义线性模型。Applied regression analysis is one of the importantprofessionalbasic coursesof studentsmajoringin Statistics.This subjectconsiders整体目标：thegeneration of random variablesand theiruse to simulate randomOverall Objectiveprocesses including Poisson processes, random walks and queuingsystems, perform numerical integration, and solve difference equations.The methods of simulation considered include acceptance-rejection,importance sampling, Monte Carlo, and the Metropolis-Hastingsalgorithm. In addition, this subject also consider t-distribution,Chi-Squared distribution,F-distribution,Estimation,Generalisedlinearmodels.仿真模拟简介1-1Introduction to simulation常见离散型和连续型随机变量的模拟：1-2 Simulation of common random variables随机变量函数的分布1-3Distributions of functions ofrandomvariablest分布；卡方分布；F分布1-4t-distribution; Chi-Squared distribution;F-distribution（1）专业目标：弱大数定律1-5Weak law of large numbersProfessional Ability参数估计1-6Estimation广义线性模型1-7Generalised linear models生灭过程和排队模型1-8Birth-death processes/Queuing models马氏链MonteCarlo(MCMC)方法1-9MarkovchainMonteCarlo (MCMC)培养遵守法律、懂规则、守规则的新时代公民2-1Cultivate citizens of the new era who abide bythe law,understand and obey the rules了解主要矛盾和次要矛盾，在面对复杂问题的时候要实事求（2）德育目标：是、抓住主要矛盾Essential Quality2-2contradictionandUnderstandthemainsecondarycontradiction, seek truth from facts and grasp the maincontradictioninthefaceofcomplexproblems2-3培养服务意识，具有“以人为本”的服务精神2 /14

2 / 14 二、教学目标 Subject Learning Objectives (SLOs) 注：毕业要求及指标点可参照悉尼学院本科生培养方案，可根据实际情况增减行数 Note: GA and index can be referred from undergraduate program in SSTC website. Please add/reduce lines based on subject. 整体目标: Overall Objective 《智能仿真建模技术》是应用统计学专业重要的专业基础课程 之一。本课程包括随机变量的生成、并用于模拟随机过程，包括泊 松过程、随机游走和排队系统、计算数值积分。 所考虑的模拟方 法包括接受-拒绝、重要性抽样、蒙特卡罗和 Metropolis-Hastings 算 法。此外还介绍统计中的三大分布，参数估计，广义线性模型。 Applied regression analysis is one of the important professional basic courses of students majoring in Statistics. This subject considers the generation of random variables and their use to simulate random processes including Poisson processes, random walks and queuing systems, perform numerical integration, and solve difference equations. The methods of simulation considered include acceptance–rejection, importance sampling, Monte Carlo, and the Metropolis-Hastings algorithm. In addition, this subject also consider t-distribution, Chi-Squared distribution, F-distribution, Estimation, Generalised linear models. （1）专业目标: Professional Ability 1-1 仿真模拟简介 Introduction to simulation 1-2 常见离散型和连续型随机变量的模拟； Simulation of common random variables 1-3 随机变量函数的分布 Distributions of functions of random variables 1-4 t 分布；卡方分布；F 分布 t-distribution; Chi-Squared distribution; F-distribution 1-5 弱大数定律 Weak law of large numbers 1-6 参数估计 Estimation 1-7 广义线性模型 Generalised linear models 1-8 生灭过程和排队模型 Birth-death processes/Queuing models 1-9 马氏链 Monte Carlo(MCMC)方法 Markov chain Monte Carlo (MCMC) （2）德育目标: Essential Quality 2-1 培养遵守法律、懂规则、守规则的新时代公民 Cultivate citizens of the new era who abide by the law, understand and obey the rules 2-2 了解主要矛盾和次要矛盾，在面对复杂问题的时候要实事求 是、抓住主要矛盾 Understand the main contradiction and secondary contradiction, seek truth from facts and grasp the main contradiction in the face of complex problems 2-3 培养服务意识，具有 “以人为本” 的服务精神

Cultivate service consciousness and have the service spirit of"people-oriented"培养具有不畏困难、不惧失败、锲而不舍、敢于尝试、迎难而上的精神，并在学习过程中培养自己的细心和耐心的勇气和精神2-4Cultivate the spirit of not fearing difficulties or failure,perseverance, daring to try,and cultivate their own careful andpatient courage and spirit in the process of learning培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成一项工作2-5Cultivateasenseof orderandplan,andcompleteawork inanorderly andgradual manner课程教学目标与毕业要求的对应关系MatrixofGA&SLOs毕业要求GA教学目标SLOs指标点GAIndex1-1：具有较强的演绎推理能力、准确计算能力、分析归纳能力、抽象思维能力，掌握数学、自然科学和相关专业知识，并使用其建立正确的数学、物理学等模型以解释复杂实际问题；1、理学知识：具有扎实的数学基础，能够将数学、自然1-2：掌握统计调查、统计数据处理、统1-1 到 1-9科学和专业知识用于解决复计分析、计算机与统计软件使用等应用杂实际问题。统计学的基本理论、知识与方法，具备采集、处理、分析数据的能力，熟悉预研报告、可行性分析报告、研究方案等文档的撰写规范；2-1：能够借助应用统计学的基本原理、方法和手段，分析、识别、表达本专业2、问题分析：能够借助应用相关的复杂实际问题：统计学的基本原理、方法和手段，识别、表达、并通过1-1 到 1-92-2：能够借助应用统计学的基本原理，文献研究分析复杂实际间方法和手段，针对复杂实际问题设计针题，以获得有效结论。对性的方案，并综合运用文献、科学理论和技术手段予以解决。11、项目管理与财务：理解11-1：掌握基本的工程管理原理和经济决并掌握工程管理原理与经济策方法，能对应用统计相关领域的新技1-1到1-9决策方法，并能在多学科环术、新应用进行技术分析和比较：境中应用。三、教学内容Content(Topics)注：以中英文填写，各部分内容的表格可根据实际知识单元数量进行复制、扩展或缩减Note: Filled in both CN and EN, extend or reduce based on the actual numbers ofknowledge unit(1)理论教学Lecture3/14

3 / 14 Cultivate service consciousness and have the service spirit of "people-oriented" 2-4 培养具有不畏困难、不惧失败、锲而不舍、敢于尝试、迎难 而上的精神，并在学习过程中培养自己的细心和耐心的勇气 和精神 Cultivate the spirit of not fearing difficulties or failure, perseverance, daring to try, and cultivate their own careful and patient courage and spirit in the process of learning 2-5 培养有条理和计划，做到心中有数、有条不紊、循序渐进地 完成一项工作 Cultivate a sense of order and plan, and complete a work in an orderly and gradual manner 课程教学目标与毕业要求的对应关系 Matrix of GA & SLOs 毕业要求 GA 指标点 GA Index 教学目标 SLOs 1、理学知识：具有扎实的数 学基础，能够将数学、自然 科学和专业知识用于解决复 杂实际问题。 1-1：具有较强的演绎推理能力、准确计 算能力、分析归纳能力、抽象思维能力， 掌握数学、自然科学和相关专业知识， 并使用其建立正确的数学、物理学等模 型以解释复杂实际问题； 1-2：掌握统计调查、统计数据处理、统 1-1 到 1-9 计分析、计算机与统计软件使用等应用 统计学的基本理论、知识与方法，具备 采集、处理、分析数据的能力，熟悉预 研报告、可行性分析报告、研究方案等 文档的撰写规范； 2、问题分析：能够借助应用 统计学的基本原理、方法和 手段，识别、表达、并通过 文献研究分析复杂实际问 题，以获得有效结论。 2-1：能够借助应用统计学的基本原理、 方法和手段，分析、识别、表达本专业 相关的复杂实际问题； 2-2：能够借助应用统计学的基本原理、 1-1 到 1-9 方法和手段，针对复杂实际问题设计针 对性的方案，并综合运用文献、科学理 论和技术手段予以解决。 11、项目管理与财务：理解 并掌握工程管理原理与经济 决策方法，并能在多学科环 境中应用。 11-1：掌握基本的工程管理原理和经济决 策方法，能对应用统计相关领域的新技 术、新应用进行技术分析和比较； 1-1 到 1-9 三、教学内容 Content (Topics) 注：以中英文填写，各部分内容的表格可根据实际知识单元数量进行复制、扩展或缩减 Note: Filled in both CN and EN, extend or reduce based on the actual numbers of knowledge unit (1) 理论教学 Lecture

知识单元序号支撑教学目标：11-1、2-4Knowledge Unit No.SLOs Supported知识单元名称仿真模拟简介Unit TitleIntroductionto simulation知识点：仿真模拟简介Knowledge DeliveryAbrief Introduction to simulation仿真模拟的背景了解:Background of simulations学习目标：Recognize仿真模拟的应用The applications of simulationsLearning Objectives理解：仿真模拟的目的UnderstandTheaimof simulations培养具有不畏困难、不惧失败、锲而不舍、敢于尝试、迎难而上的精神，并在学习过程中培养自己的细心和耐心的勇气和精神Cultivate the spirit of notfearing difficulties or failure,perseverance,daring to try, and cultivate their own careful and patient courage andspirit in the process of learning德育目标培养服务意识，具有“以人为本”的服务精神Moral ObjectivesCultivate service consciousness and have the service spirit of"people-oriented"培养遵守法律、懂规则、守规则的新时代公民Cultivate citizens of the new era who abide bythe law, understand andobey the rules重点：仿真模拟的目的Key PointsThe aim of simulation难点：仿真模拟的应用Focal PointsTheapplications of simulations知识单元序号支撑教学目标：21-2, 2-2Knowledge Unit No.SLOs Supported知识单元名称常见离散型和连续型随机变量的模拟Unit TitleSimulation of common random variables贝努利分布、二项分布、几何分布的模拟Simulation of Bernoulli, binomial and geometric variables知识点：Knowledge Delivery指数分布、波松分布的模拟；Simulationofexponential and Poisson randomvariables贝努利分布、二项分布、几何分布的模拟Simulation of Bernoulli,binomialandgeometric理解：variables学习目标：Understand指数分布、波松分布的模拟；Learning ObjectivesSimulation of exponential and Poisson random variables掌握：贝努利分布、二项分布、几何分布的模拟MasterSimulation of Bernoulli,binomial andgeometric4/14

4 / 14 知识单元序号: Knowledge Unit No. 1 支撑教学目标: SLOs Supported 1-1、2-4 知识单元名称 Unit Title 仿真模拟简介 Introduction to simulation 知识点: Knowledge Delivery 仿真模拟简介 A brief Introduction to simulation 学习目标: Learning Objectives 了解: Recognize 仿真模拟的背景 Background of simulations 仿真模拟的应用 The applications of simulations 理解: Understand 仿真模拟的目的 The aim of simulations 德育目标 Moral Objectives 培养具有不畏困难、不惧失败、锲而不舍、敢于尝试、迎难而上的 精神，并在学习过程中培养自己的细心和耐心的勇气和精神 Cultivate the spirit of not fearing difficulties or failure, perseverance, daring to try, and cultivate their own careful and patient courage and spirit in the process of learning 培养服务意识，具有 “以人为本” 的服务精神 Cultivate service consciousness and have the service spirit of "people-oriented" 培养遵守法律、懂规则、守规则的新时代公民 Cultivate citizens of the new era who abide by the law, understand and obey the rules 重点: Key Points 仿真模拟的目的 The aim of simulation 难点: Focal Points 仿真模拟的应用 The applications of simulations 知识单元序号: Knowledge Unit No. 2 支撑教学目标: SLOs Supported 1-2，2-2 知识单元名称 Unit Title 常见离散型和连续型随机变量的模拟 Simulation of common random variables 知识点: Knowledge Delivery 贝努利分布、二项分布、几何分布的模拟 Simulation of Bernoulli, binomial and geometric variables 指数分布、波松分布的模拟； Simulation of exponential and Poisson random variables 学习目标: Learning Objectives 理解: Understand 贝努利分布、二项分布、几何分布的模拟 Simulation of Bernoulli, binomial and geometric variables 指数分布、波松分布的模拟； Simulation of exponential and Poisson random variables 掌握: Master 贝努利分布、二项分布、几何分布的模拟 Simulation of Bernoulli, binomial and geometric

variables指数分布、波松分布的模拟；Simulation of exponential and Poisson random variables了解主要矛盾和次要矛盾，在面对复杂问题的时候要实事求是、抓住主要矛盾德育目标Understand the main contradiction and secondary contradiction, seekMoral Objectivestruth from facts and grasp the main contradiction in the face ofcomplexproblems贝努利分布、二项分布、几何分布的模拟重点：Simulationof Bernoulli,binomial andgeometricvariablesKey Points指数分布、波松分布的模拟；Simulationof exponential andPoissonrandomvariables贝努利分布、二项分布、几何分布的模拟难点：Simulation of Bernoulli,binomial andgeometricvariablesFocal points指数分布、波松分布的模拟：Simulation ofexponential and Poisson random variables支撑教学目标：知识单元序号：31-3, 2-5SLOs SupportedKnowledgeUnitNo知识单元名称随机变量函数的分布Unit TitleDistributions of functions of random variables多维变量分布知识点：MultivariatedistributionsKnowledge Delivery随机变量函数的分布Distributions of functions of random variables了解：多维变量分布RecognizeMultivariatedistributions学习目标：理解：随机变量函数的分布Learning ObjectivesUnderstandDistributions of functions of random variables掌握随机变量函数的分布MasterDistributions of functions ofrandom variables培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成德育目标项工作Moral ObjectivesCultivate a sense of order and plan, and complete a work in an orderlyand gradual manner重点：随机变量函数的分布Key PointsDistributions of functions of random variables难点：随机变量函数的分布Focal pointsDistributionsoffunctionsof randomvariables知识单元序号支撑教学目标：41-4, 2-3Knowledge Unit No.SLOs Supported知识单元名称t分布、卡方分布和F分布Unit Titlet-distribution, Chi-Squared distribution and F-distribution5/14

5 / 14 variables 指数分布、波松分布的模拟； Simulation of exponential and Poisson random variables 德育目标 Moral Objectives 了解主要矛盾和次要矛盾，在面对复杂问题的时候要实事求是、抓 住主要矛盾 Understand the main contradiction and secondary contradiction, seek truth from facts and grasp the main contradiction in the face of complex problems 重点: Key Points 贝努利分布、二项分布、几何分布的模拟 Simulation of Bernoulli, binomial and geometric variables 指数分布、波松分布的模拟； Simulation of exponential and Poisson random variables 难点: Focal points 贝努利分布、二项分布、几何分布的模拟 Simulation of Bernoulli, binomial and geometric variables 指数分布、波松分布的模拟； Simulation of exponential and Poisson random variables 知识单元序号: Knowledge Unit No. 3 支撑教学目标: SLOs Supported 1-3，2-5 知识单元名称 Unit Title 随机变量函数的分布 Distributions of functions of random variables 知识点: Knowledge Delivery 多维变量分布 Multivariate distributions 随机变量函数的分布 Distributions of functions of random variables 学习目标: Learning Objectives 了解: Recognize 多维变量分布 Multivariate distributions 理解: Understand 随机变量函数的分布 Distributions of functions of random variables 掌握: Master 随机变量函数的分布 Distributions of functions of random variables 德育目标 Moral Objectives 培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成一 项工作 Cultivate a sense of order and plan, and complete a work in an orderly and gradual manner 重点: Key Points 随机变量函数的分布 Distributions of functions of random variables 难点: Focal points 随机变量函数的分布 Distributions of functions of random variables 知识单元序号: Knowledge Unit No. 4 支撑教学目标: SLOs Supported 1-4，2-3 知识单元名称 Unit Title t 分布、卡方分布和 F 分布 t-distribution, Chi-Squared distribution and F-distribution

t分布t-distribution卡方分布知识点：Chi-Squared distributionKnowledge DeliveryF分布F-distribution三个分布的构成理解：Construction of t-distribution, Chi-Squared distribution学习目标：Understandand F-distributionLearning Objectives三个分布的构成掌握：Construction of t-distribution, Chi-Squared distributionMasterand F-distribution培养服务意识，具有“以人为本”的服务精神德育目标Cultivate service consciousness and have the service spirit ofMoral Objectives"people-oriented"三个分布的构成重点：Construction of t-distribution,Chi-Squareddistribution andKey PointsF-distribution三个分布的构成难点：Construction oft-distribution,Chi-Squared distribution andFocal pointsF-distribution知识单元序号支撑教学目标：51-5, 2-3Knowledge Unit No.SLOs Supported知识单元名称弱大数定律Unit TitleWeaklawof largenumbers弱大数定律Weak law of large numbers知识点：Markov和Chebyshev不等式Knowledge DeliveryMarkov and Chebyshev inequalitiesMonteCarlo方法计算定积分Monte Carlo method for definite integrals弱大数定律了解：Weak lawof large numbersMarkov和Chebyshev不等式Recognize学习目标MarkovandChebyshevinequalitiesLearning Objectives理解：Monte Carlo方法计算定积分UnderstandMonte Carlo method for definite integrals掌握：MonteCarlo方法计算定积分MasterMonteCarlomethodfordefinite integrals培养服务意识，具有“以人为本”的服务精神德育目标Cultivate service consciousness and have the service spirit ofMoral Objectives"people-oriented"6 / 14

6 / 14 知识点: Knowledge Delivery t 分布 t-distribution 卡方分布 Chi-Squared distribution F 分布 F-distribution 学习目标: Learning Objectives 理解: Understand 三个分布的构成 Construction of t-distribution, Chi-Squared distribution and F-distribution 掌握: Master 三个分布的构成 Construction of t-distribution, Chi-Squared distribution and F-distribution 德育目标 Moral Objectives 培养服务意识，具有 “以人为本” 的服务精神 Cultivate service consciousness and have the service spirit of "people-oriented" 重点: Key Points 三个分布的构成 Construction of t-distribution, Chi-Squared distribution and F-distribution 难点: Focal points 三个分布的构成 Construction of t-distribution, Chi-Squared distribution and F-distribution 知识单元序号: Knowledge Unit No. 5 支撑教学目标: SLOs Supported 1-5，2-3 知识单元名称 Unit Title 弱大数定律 Weak law of large numbers 知识点: Knowledge Delivery 弱大数定律 Weak law of large numbers Markov 和 Chebyshev 不等式 Markov and Chebyshev inequalities Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 学习目标: Learning Objectives 了解: Recognize 弱大数定律 Weak law of large numbers Markov 和 Chebyshev 不等式 Markov and Chebyshev inequalities 理解: Understand Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 掌握: Master Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 德育目标 Moral Objectives 培养服务意识，具有 “以人为本” 的服务精神 Cultivate service consciousness and have the service spirit of "people-oriented

重点：MonteCarlo方法计算定积分Key PointsMonte Carlo method for definite integrals难点：MonteCarlo方法计算定积分Focal pointsMonte Carlo method for definite integrals知识单元序号支撑教学目标：61-6, 2-5Knowledge Unit No.SLOs Supported参数估计知识单元名称Unit TitleEstimation矩估计和最大似然估计Method of moments;Maximum likelihoodestimation线性回归Linear regression最小二乘估计知识点：Least squares estimationKnowledge Delivery置信区间Confidence intervals;预测区间Prediction intervals;偏差Bias预测区间了解:Prediction intervals;偏差RecognizeBias最小二乘估计理解：Least squares estimation学习目标：置信区间UnderstandLearning ObjectivesConfidence intervals;矩估计和最大似然估计Method of moments;掌握：MaximumlikelihoodestimationMaster线性回归Linear regression培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成德育目标项工作Moral ObjectivesCultivate a sense of order and plan, and complete a work in an orderlyand gradual manner矩估计和最大似然估计Method of moments;重点：Maximum likelihood estimationKey Points线性回归Linear regression7 / 14

7 / 14 重点: Key Points Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 难点: Focal points Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 知识单元序号: Knowledge Unit No. 6 支撑教学目标: SLOs Supported 1-6，2-5 知识单元名称 Unit Title 参数估计 Estimation 知识点: Knowledge Delivery 矩估计和最大似然估计 Method of moments; Maximum likelihood estimation 线性回归 Linear regression 最小二乘估计 Least squares estimation 置信区间 Confidence intervals; 预测区间 Prediction intervals; 偏差 Bias 学习目标: Learning Objectives 了解: Recognize 预测区间 Prediction intervals; 偏差 Bias 理解: Understand 最小二乘估计 Least squares estimation 置信区间 Confidence intervals; 掌握: Master 矩估计和最大似然估计 Method of moments; Maximum likelihood estimation 线性回归 Linear regression 德育目标 Moral Objectives 培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成一 项工作 Cultivate a sense of order and plan, and complete a work in an orderly and gradual manner 重点: Key Points 矩估计和最大似然估计 Method of moments; Maximum likelihood estimation 线性回归 Linear regression

难点：矩估计和最大似然估计Focal pointsMethod of moments and Maximum likelihood estimation知识单元序号：支撑教学目标：71-7, 2-1Knowledge Unit No.SLOs Supported知识单元名称广义线性模型Unit TitleGeneralised linear models广义线性模型知识点：Generalised linear modelsKnowledge Delivery指数族Exponential family广义线性模型理解：Generalised linear modelsUnderstand指数族学习目标：Exponential familyLearning Objectives广义线性模型掌握：Generalised linear modelsMaster指数族Exponential family培养遵守法律、懂规则、守规则的新时代公民德育目标Cultivate citizens of the new era who abide by the law, understand andMoral Objectivesobey the rules重点：指数族Key PointsExponential family难点：广义线性模型Focal pointsGeneralised linearmodels知识单元序号：支撑教学目标：81-8, 2-5Knowledge Unit No.SLOs Supported知识单元名称生灭过程和排队模型Unit TitleBirth-death processes and queuing models生灭过程知识点：Birth-death processesKnowledge Delivery排队模型Queuing models生灭过程Birth-deathprocesses学习目标：理解：排队模型Learning ObjectivesUnderstandQueuing models培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成德育目标项工作Moral ObjectivesCultivate a sense of order and plan, and complete a work in an orderlyand gradual manner8 / 14

8 / 14 难点: Focal points 矩估计和最大似然估计 Method of moments and Maximum likelihood estimation 知识单元序号: Knowledge Unit No. 7 支撑教学目标: SLOs Supported 1-7，2-1 知识单元名称 Unit Title 广义线性模型 Generalised linear models 知识点: Knowledge Delivery 广义线性模型 Generalised linear models 指数族 Exponential family 学习目标: Learning Objectives 理解: Understand 广义线性模型 Generalised linear models 指数族 Exponential family 掌握: Master 广义线性模型 Generalised linear models 指数族 Exponential family 德育目标 Moral Objectives 培养遵守法律、懂规则、守规则的新时代公民 Cultivate citizens of the new era who abide by the law, understand and obey the rules 重点: Key Points 指数族 Exponential family 难点: Focal points 广义线性模型 Generalised linear models 知识单元序号: Knowledge Unit No. 8 支撑教学目标: SLOs Supported 1-8，2-5 知识单元名称 Unit Title 生灭过程和排队模型 Birth-death processes and queuing models 知识点: Knowledge Delivery 生灭过程 Birth-death processes 排队模型 Queuing models 学习目标: Learning Objectives 理解: Understand 生灭过程 Birth-death processes 排队模型 Queuing models 德育目标 Moral Objectives 培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成一 项工作 Cultivate a sense of order and plan, and complete a work in an orderly and gradual manner

重点：生灭过程Key PointsBirth-death processes难点：排队模型Focal pointsQueuingmodels支撑教学目标：知识单元序号91-9, 2-5SLOs SupportedKnowledge Unit No知识单元名称马氏链MonteCarlo(MCMC)方法Unit TitleMarkovchainMonteCarlo (MCMC)马氏链MonteCarlo(MCMC)方法MarkovchainMonteCarlo (MCMC)Metropolis-Hastings方法知识点：Metropolis-Hastings algorithmKnowledge DeliveryMCMC诊断MCMC Diagnostics贝叶斯推断和共轭先验Bayesianinferenceandconjugatepriors了解:MCMC诊断MCMC DiagnosticsRecognize马氏链MonteCarlo(MCMC)方法理解：MarkovchainMonteCarlo(MCMC)学习目标：UnderstandMetropolis-Hastings方法Learning ObjectivesMetropolis-Hastings algorithmMetropolis-Hastings方法掌握：Metropolis-Hastings algorithmMaster贝叶斯推断和共轭先验Bayesian inference and conjugate priors培养有条理和计划，做到心中有数、有条不素、循序渐进地完成项工作德育目标Moral ObjectivesCultivatea senseoforderandplan,and completeawork in an orderlyand gradual manner重点：马氏链MonteCarlo(MCMC)方法Key PointsMarkov chain MonteCarlo (MCMC)难点：贝叶斯推断和共轭先验Focal pointsBayesian inference and conjugatepriors(2）实验教学Experiments注：可根据实际情况增减行数。实验类型可分为验证性、设计性、综合性，实验性质可分为选做、必做。Note: Please add/reduce lines based on subject. The Type contains Verify, Design, and Comprehensive, while the Patterncontains Required and Elective序号学时每组人数实验项目名称实验类型实验性质No.HoursMPG*TypePatternExperiment Topic9/14

9 / 14 重点: Key Points 生灭过程 Birth-death processes 难点: Focal points 排队模型 Queuing models 知识单元序号: Knowledge Unit No. 9 支撑教学目标: SLOs Supported 1-9，2-5 知识单元名称 Unit Title 马氏链 Monte Carlo(MCMC)方法 Markov chain Monte Carlo (MCMC) 知识点: Knowledge Delivery 马氏链 Monte Carlo(MCMC)方法 Markov chain Monte Carlo (MCMC) Metropolis-Hastings 方法 Metropolis-Hastings algorithm MCMC 诊断 MCMC Diagnostics 贝叶斯推断和共轭先验 Bayesian inference and conjugate priors 学习目标: Learning Objectives 了解: Recognize MCMC 诊断 MCMC Diagnostics 理解: Understand 马氏链 Monte Carlo(MCMC)方法 Markov chain Monte Carlo (MCMC) Metropolis-Hastings 方法 Metropolis-Hastings algorithm 掌握: Master Metropolis-Hastings 方法 Metropolis-Hastings algorithm 贝叶斯推断和共轭先验 Bayesian inference and conjugate priors 德育目标 Moral Objectives 培养有条理和计划，做到心中有数、有条不紊、循序渐进地完成一 项工作 Cultivate a sense of order and plan, and complete a work in an orderly and gradual manner 重点: Key Points 马氏链 Monte Carlo(MCMC)方法 Markov chain Monte Carlo (MCMC) 难点: Focal points 贝叶斯推断和共轭先验 Bayesian inference and conjugate priors (2) 实验教学 Experiments 注：可根据实际情况增减行数。实验类型可分为验证性、设计性、综合性，实验性质可分为选做、必做。 Note: Please add/reduce lines based on subject. The Type contains Verify, Design, and Comprehensive, while the Pattern contains Required and Elective 序号 No. 实验项目名称 Experiment Topic 学时 Hours 每组人数 MPG* 实验类型 Type 实验性质 Pattern

离散事件、离散型变量、连续型随机变量模拟验证性必做21Discrete event and discrete variableVerifyElecsimulation;Simulation of continuousrandom variablesMonteCarlo方法计算定积分验证性必做22Monte Carlo method for definite-VerifyElecintegrals马氏MonteCarlo(MCMC)方法；Metropolis-Hastings方法验证性必做321MarkovchainMonteCarloVerifyElec(MCMC)Metropolis-Hastingsalgorithm6总计Total*MPG: Members per group实验项目序号：支撑教学目标：11-2SLOs SupportedExperiment No每组成员：指导教师：胡海娟1TutorHaijuan HuMembersperGroup实验名称：常见随机变量模拟Experiment TitleSimulationof common random variables离散事件、离散型变量、连续型随机变量模拟实验内容：Discreteevent and discretevariable simulation and simulation ofContentcontinuous randomvariables学习目标掌握常见随机变量的模拟方法Learning ObjectivesMasterthemethodof Simulation of commonrandomvariables教学要求：会模拟常见的随机变量。RequirementsKnowhowtosimulatecommonrandomvariables实验场地实验室/机房（科技楼5082）LocationComputer room5082实验软硬件设备计算机Software/HardwareComputer实验项目序号：支撑教学目标：21-5Experiment NoSLOs Supported每组成员指导教师：胡海娟1TutorMembers per GroupHaijuan Hu实验名称：MonteCarlo方法计算定积分Experiment TitleMonteCarlomethodfordefiniteintegrals实验内容用MonteCarlo方法计算定积分ContentMonte Carlomethod fordefinite integrals10/14

10 / 14 1 离散事件、离散型变量、连续型随 机变量模拟 Discrete event and discrete variable simulation;Simulation of continuous random variables 2 1 验证性 Verify 必做 Elec 2 Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 2 1 验证性 Verify 必做 Elec 3 马氏 Monte Carlo(MCMC)方法； Metropolis-Hastings 方法 Markov chain Monte Carlo (MCMC) ; Metropolis-Hastings algorithm 2 1 验证性 Verify 必做 Elec 总计 Total 6 *MPG: Members per group 实验项目序号: Experiment No. 1 支撑教学目标: SLOs Supported 1-2 每组成员: Members per Group 1 指导教师: Tutor 胡海娟 Haijuan Hu 实验名称: Experiment Title 常见随机变量模拟 Simulation of common random variables 实验内容: Content 离散事件、离散型变量、连续型随机变量模拟 Discrete event and discrete variable simulation and simulation of continuous random variables 学习目标: Learning Objectives 掌握常见随机变量的模拟方法 Master the method of Simulation of common random variables 教学要求: Requirements 会模拟常见的随机变量。 Know how to simulate common random variables 实验场地: Location 实验室/机房 （科技楼 5082） Computer room 5082 实验软硬件设备: Software/Hardware 计算机 Computer 实验项目序号: Experiment No. 2 支撑教学目标: SLOs Supported 1-5 每组成员: Members per Group 1 指导教师: Tutor 胡海娟 Haijuan Hu 实验名称: Experiment Title Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals 实验内容: Content 用 Monte Carlo 方法计算定积分 Monte Carlo method for definite integrals