2022级统计学(理学)硕士研究生培养方案
所属学科门类:理学
所属一级学科:统计学
所属院系:统计与信息学院
一、培养目标
本专业旨在培养德才兼备,具有家国情怀和国际视野,具备良好政治素质与职业道德,拥有坚实的统计学、数学、经济学理论基础,掌握现代统计分析方法和相关计算机技术,在经济、金融与商务等领域,熟练地运用现代统计、计量分析和大数据分析等方法解决经济系统中相关问题的复合型与开放型专业人才。
二、学制
本专业学制为2.5年。在规定时期完成课程学习,但未完成学位论文者,可申请延长学习年限,累计最长学习年限不得超过4.5年。
三、研究方向
1.数理统计学
2.社会经济统计学
3.金融统计、风险管理与精算学
4.数据科学与商务统计
四、课程设置与学分要求
本专业硕士研究生在攻读硕士学位期间应修满38学分,其中包括公共课7学分,学位基础课18学分,专业选修课8学分,跨专业选修课2学分,名师讲座2学分,社会实践1学分。此外,本专业硕士研究生必须通过国家英语六级考试,或者经相同水平的英语测试,达到合格要求。具体课程安排和学分见附表。
五、社会实践
根据本专业的培养方案,对于统计学高级研究人才的培养,要求掌握概率论、统计推断、统计编程等基础课和专业课,并具备将所学知识应用在科学研究中的应用能力。
对于统计学人才的培养,要求学生在研究生期间参加一定的社会实践。通过社会实践,培养学生的实践能力、分析问题和解决问题的能力以及综合运用所学基础知识和基本技能的能力,同时也为增强学生适应社会的能力和就业竞争力。社会实践的考核方式主要包括以下几个方面:(1)运用统计学知识分析和思考社会实践过程中发生的事情;(2)将社会实践中的经验与教训总结成案例;(3)掌握与实习单位有关行业的基本知识与基本技能;(4)总结有关行业的管理知识与基本技能。成果是围绕上述内容写一篇社会实践报告。
具体要求见《纽约国际588888线路检测中心硕士研究生社会实践实施细则》。
六、科研能力
为了提高研究生学术科研能力,发挥研究生导师的研究指导作用,研究生在校期间必须在导师的指导下,从事科学研究,提高学术素养。
七、培养方式
统计学专业的课程均采取讲授、讨论和专题研究的方式进行,对硕士研究生的培养实行导师负责制。
八、学位论文
研究生必须按规定时间完成学位论文撰写,经导师同意推荐答辩并通过校、院组织的论文盲审和答辩,论文质量达到所申请学位的合格要求。具体要求见《纽约国际588888线路检测中心硕士学位管理办法实施细则》。学位论文的写作要求见《纽约国际588888线路检测中心硕士学位论文内容和格式要求(2020年修订)》。
附表:
课程名称 | 第1学期 | 第2学期 | 第3学期 | 学时 | 学分 | 开课部门 | ||
公共课 | 中国特色社会主义理论与实践研究 | 2 |
|
| 36 | 2 | 马克思主义学院 | |
马克思主义与社会科学方法论研究 | 1 |
|
| 18 | 1 | 马克思主义学院 | ||
高级英语口语与写作 |
| 2 |
| 36 | 2 | 国际商务外语学院 | ||
统计软件(英) | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
学位基础课 | 学术规范与论文写作 |
| 1 |
| 18 | 1 | 统计与信息学院 | |
统计学前沿文献导读 |
| 1 |
| 18 | 1 | 统计与信息学院 | ||
高等统计学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
高等概率论 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
2 |
|
| 36 | 2 | 统计与信息学院 | |||
高级计量经济学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
机器学习 |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
统计计算 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
选修 课 | 理 论 型 | 数据分析与统计建模 | 2 |
|
| 36 | 2 | 统计与信息学院 |
贝叶斯统计 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
随机过程 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
线性模型理论 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
非参数统计 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
高级计量经济学(II) |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
金融工程 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
数理金融 |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
多元统计分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
时间序列分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
试验设计与建模 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
抽样理论与应用 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
应 用 型 | 优化方法与数据分析实践 | 2 |
|
| 36 | 2 | 统计与信息学院 | |
金融计量学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
复杂数据统计分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
广义线性与混合效应模型(英) |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
| 2 |
| 36 | 2 | 统计与信息学院 | |||
国际贸易统计调查 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
社会网络分析与计算方法 |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
商务大数据案例分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
算法设计与实践 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
分布式计算 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
高级数据库技术 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
高频数据与量化交易 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
全球价值链统计 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
复杂系统与复杂网络 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
神经网络与深度学习 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
强化学习基础 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
跨 专 业 | 国际贸易实务 |
| 2 |
| 36 | 3 | 国际经贸学院 | |
电子商务 |
|
| 2 | 36 | 2 | 国际经贸学院 | ||
人口、资源和环境经济学 |
|
| 2 | 36 | 2 | 国际经贸学院 | ||
财务管理研究 |
| 2 |
| 36 | 2 | 会计学院 | ||
市场营销专题 |
| 2 |
| 36 | 2 | 工商管理学院 | ||
心理与行为研究方法 |
|
| 2 | 36 | 2 | 工商管理学院 | ||
服务贸易与全球价值链 |
| 2 |
| 36 | 2 | 贸易谈判学院 | ||
固定收益证券研究 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
金融风险管理 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
投资学 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
名师讲座 | 8次 | 2 |
| |||||
社会实践 |
|
|
|
| 1 |
|
MasterPrograminStatistics for2022
Field:Science
Discipline:Statistics
School:School of Statistics and Information
I.Objectives
Thismajor aims to cultivate compound and open professionals who have bothability and political integrity, have the feelings of home andcountry and international vision, have good political quality andprofessional ethics, have a solid theoretical foundation instatistics, mathematics and economics, master modern statisticalanalysis methods and related computer technologies, and skillfullyuse modern statistics, econometric analysis and big data analysismethods to solve related problems in the economic system in thefields of economy, finance and commerce.
II.Duration of the Program
Theduration of the program is 2.5 years. Students who have successfullycompleted the coursework within the required time but have notcompleted their dissertation can apply for an extension. Thecumulative maximum length of study shall not exceed 4.5 years.
III.Research Areas
1.Mathematical Statistics
2.Socio-economic Statistics
3.Financial Statistics, Risk Management and Actuarial Science
4.Data Science and Business Statistics
IV.Courses and Credits
Allstudents must earn 38 credits, including 7 “common required course”credits, 18 “required course” credits, 8 “major optionalcourse” credits, 2 “cross-specialty optional course” credits,2 “lecturecourse” credits and 1“social practice” credit. In addition,master candidates in this program must pass College English Test(CET) 6 or an equivalent test of English language proficiency tofulfil the requirement for graduation. Specific course structure canbe found in the appendix.
V.Social Practice
Accordingto the program, students who are going to be researchers are requiredto have a good knowledge of probability theory, statisticalinference, statistical methods and statistical programming. They arealso required to apply the knowledge in scientific research.
Forstudents who are going to be practical personnel, they are requiredto take part in social practice. Through social practice, studentscan be equipped with practical abilities to analyze and solveproblems by using the basic knowledge and skills they have learned inthis program, and hence, enhance their social adaptability andemployment competitiveness. Social practice is to be assessed bycompleting a report covering the following points: 1) Analyze andconsider the events occurring in social practice by using the scienceof statistics. 2) Sum up the experiences and lessons in socialpractice for case studies. 3) Be familiar with the basic knowledgeand skill of the internship and the relevant industry. 4) Summarizethe management knowledge and skills of the relevant industry.
Forspecific requirements, please refer to the Detailed Rules for “theImplementation of social practice for master's degree students ofShanghai University of International Business and Economics”.
VI.Academic Training
Inorder to improve the academic research ability of graduate studentsand give full play to the research guidance role of graduate tutors,graduate students must engage in scientific research and improvetheir academic literacy under the guidance of their tutors.
VII.Education Modes
Allthe courses will take the forms of intensive lectures, discussionsand study in special topics. Master supervisors are responsible forthe cultivation of their master students.
VIII.Dissertation
Graduatestudents must complete the dissertation writing in accordance withthe prescribed time, and with the consent of the supervisor,recommend the defense and pass the thesis defense organized by theuniversity and the college, and the quality level of the thesis meetsthe qualified requirements of the applied degree. For specificrequirements, please refer to the “Detailed Rules for theImplementation of the Measures for the Administration of Master'sDegrees of Shanghai University of International Business andEconomics”. For the writing requirements of the dissertation,please refer to the “Content and Format Requirements for theMaster's Thesis of Shanghai University of International Business andEconomics (Revised in 2020)”.
AttachedTable:
Category | Course Name | Semester | Credit Hours | Credit | Department | |||
1 | 2 | 3 | ||||||
Required Courses | Socialist Theory and Practice with Chinese Characteristics (Degree Course) | 2 |
|
| 36 | 2 | School of Marxism | |
Research on Marxism and Methodology of Social Science | 1 |
|
| 18 | 1 | School of Marxism | ||
Advanced Speaking & Writing |
| 2 |
| 36 | 2 | School of Languages | ||
Statistical Software(English) | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Required Courses | Academic Standards and Paper Writing |
| 1 |
| 18 | 1 | School of Statistics and Information | |
Introduction to frontier literature of statistics |
| 1 |
| 18 | 1 | School of Statistics and Information | ||
Advanced Statistics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Advanced Probability | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Advanced Programming | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Advanced Econometrics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Machine Learning |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Statistical Computing |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Optional Courses | Theoretical | Data Analysis and Statistical Model | 2 |
|
| 36 | 2 | School of Statistics and Information |
Bayesian Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Random Process |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Linear Model |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Nonparametric Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Advanced Econometrics (II) |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Financial Engineering |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Mathematical Finance |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Multivariate Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Time Series Analysis |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Experimental Design and Modeling |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Sampling Theory and Application |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Applied | Optimization Methods and Data Analysis Applications | 2 |
|
| 36 | 2 | School of Statistics and Information | |
Financial Econometrics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Statistical Analysis of Complex Data |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Generalized Linear Model and Mixed Effects Model |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Theory and Application of Spatio-Temporal Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
International Trade Statistics Research |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Social Network Analysis and Calculation Methods |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Analysis of Big Data Cases |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Introduction to Algorithms |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Algorithm Design and Practice |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Distributed Computing |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Advanced Database Technology |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Global Value Chain Statistics |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
High-Frequency Trading and Quantitative Finance |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Complex System and Networks |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Neutral Network and Deep Learning |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Reinforcement Learning |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Cross-Specialty | Practice of Import and Export |
| 2 |
| 36 | 2 | School of Business | |
Electronic Commerce |
|
| 2 | 36 | 2 | School of Business | ||
Population, Resource and Environmental Economics |
|
| 2 | 36 | 2 | School of Business | ||
Research on Financial Management |
| 2 |
| 36 | 2 | School of Accounting | ||
Monographic Study on Marketing Management |
| 2 |
| 36 | 2 | School of Management | ||
Empirical Methods in Psychology and Behavior Research |
|
| 2 | 36 | 2 | School of Management | ||
Services Trade and Global Value Chain |
| 2 |
| 36 | 2 | School of Trade Negotiation | ||
Fixed Income Securities Research |
|
| 2 | 36 | 2 | School of Finance | ||
Financial Risk Management |
|
| 2 | 36 | 2 | School of Finance | ||
Investment |
|
| 2 | 36 | 2 | School of Finance | ||
Lectures | eight times | 2 | School of Statistics and Information | |||||
Social Practice |
| 1 | School of Statistics and Information |