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2020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

本专业旨在培养具有良好政治素质与道德修养,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,在贸易、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与挖掘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、数据科学与统计计算

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40学分,其中包括公共必修课7学分,学位基础课20学分,选修课10学分(其中跨专业选修课最少必须选择2学分),名师讲座2学分,社会实践1学分。具体课程安排和学分见附表

五、社会实践及科研能力的培养

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)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。

为了提高研究生科研能力,发挥研究生导师的指导作用,研究生在校期间必须在导师的指导下,从事统计科学研究,并在学术期刊上以第一作者身份或第二作者身份(导师为第一作者)公开发表学术论文一篇及以上,此为研究生学位申请的必要条件之一。

六、培养方式与成绩考核

 

六、培养方式与成绩考核

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。

七、学位论文

硕士研究生的学位论文开题报告应在第四学期初完成,由本学科硕士生指导小组组织进行。学位论文的写作要求见《必赢626net入口首页硕士学位论文内容和格式要求2013年修订)


附表:

类别

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(学位课)

 

 

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

外语学院

统计软件(英)

2

 

 

36

2

统信学院

学位基础课

高等统计学

3

 

 

54

3

统信学院

高等概率论

3

 

 

54

3

统信学院

高级程序设计

3

 

 

54

3

统信学院

线性模型理论

 

2

 

36

2

统信学院

多元统计分析

 

2

 

36

2

统信学院

时间序列分析

 

2

 

36

2

统信学院

统计学习

 

3

 

54

3

统信学院

非参数统计

 

 

2

36

2

统信学院

选修

理论型

贝叶斯统计

 

2

 

36

2

统信学院

统计计算

 

2

 

36

2

统信学院

金融数学

 

2

 

36

2

统信学院

寿险精算数学(英)

 

 

2

36

2

统信学院

精算模型

 

 

2

36

2

统信学院

试验设计与建模

 

 

2

36

2

统信学院

抽样理论与应用

 

 

2

36

2

统信学院

应用型

生存分析

 

2

 

36

2

统信学院

空间统计学

 

2

 

36

2

统信学院

数据挖掘

 

3

 

54

3

统信学院

高级数据库技术

 

3

 

54

3

统信学院

算法导论

 

2

 

36

2

统信学院

统计软件SAS

 

2

 

36

2

统信学院

风险管理

 

 

2

36

2

统信学院

广义线性与混合效应模型(英)

 

 

2

36

2

统信学院

复杂数据分析

 

 

2

36

2

统信学院

跨专业(最少必须选修2学分)

国际物流与供应链管理

 

 

2

36

2

经贸学院

电子商务

 

 

2

36

2

经贸学院

市场营销专题

 

2

 

36

2

工商管理学院

消费者行为专题

 

2

 

36

2

工商管理学院

金融计量学

 

3

 

54

3

金融学院

金融工程研究

 

2

 

36

2

金融学院

公司金融研究

 

2

 

36

2

金融学院

固定收益证券研究

 

 

2

36

2

金融学院

国际金融研究

 

 

2

36

2

金融学院

投资学

 

 

2

36

2

金融学院

名师讲座

 

 

8次

2

统信学院

社会实践

 

 

 

 

 

 

1

统信学院

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Master Program in Statistics 2020

 

Field: Science

Discipline: Statistics

School: School of Statistics and Information

 

I. Objectives

The aim of this program is to cultivate complex and open professionals with good political quality and moral cultivation, solid theoretical basis in statistics, mathematics and economics, modern statistical methods and related computer technology, and skillful use of modern statistics and big data analysis to solve problems related to the economic system in the fields of trade, finance and business.

II. Duration of the Program

The duration of the program is 2.5 years. Students who have successfully completed the coursework within the required time but have not completed their dissertation can apply for an extension of no more than one year.

III. Field of Research

1. Mathematical Statistics

2. Socio-economic Statistics

3. Financial Statistics, Risk Management and Actuarial Science

4. Data Science and Statistical Computing

IV. Courses and Credits

All students must earn 40 credits, including 7 “common required course” credits, 20 “required course” credits, 10 “optional course” credits (including 2 or more cross-specialty optional course” credits)  2 “lecture course” credits and 1social practice” credit. Specific course structure can be found in the appendix.

V. Occupational Apprenticeship and Academic Training

According to the program, students who are going to be researchers are required to have a good knowledge of probability theory, statistical inference, statistical methods and statistical programming. They are also required to apply the knowledge in scientific research.

For students who are going to be practical personnel, they are required to take part in social practice. Through social practice, students can be equipped with practical abilities to analyze and solve problems by using the basic knowledge and skills they have learned in this program, and hence, enhance their social adaptability and employment competitiveness. Social practice is to be assessed by completing a report covering the following points: 1) Analyze and consider the events occurring in social practice by using the science of statistics. 2) Sum up the experiences and lessons in social practice for case studies. 3) Be familiar with the basic knowledge and skill of the internship and the relevant industry. 4) Summarize the management knowledge and skills of the relevant industry.

To enhance postgraduate students' academic and scientific capability, postgraduate students during his or her school period are required to undertake scientific research under his or her supervisor’s instruction and gain the supervisor's approval.

VI. Education Modes and Performance Assessment

All the courses will take the forms of intensive lectures, discussions and study in special topics. Master supervisors are responsible for the cultivation of their master students.

VII. Dissertation

The proposal for dissertation should be completed at the beginning of the 4th semester, with the guidance by members of a panel. Please refer to “Layout Requirements for Graduates of Shanghai University of International Business and Economics (revised edition 2013)” for details.


Attached Table

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

R Language and Statistical Software

2

 

 

36

2

School of Statistics and Information

Required Courses

Advanced Statistics

3

 

 

54

3

School of Statistics and Information

Advanced Probability

3

 

 

54

3

School of Statistics and Information

Advanced Programming

3

 

 

54

3

School of Statistics and Information

Linear Model

 

2

 

36

2

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

Statistical Learning

 

3

 

54

3

School of Statistics and Information

Nonparametric Statistics

 

 

2

36

2

School of Statistics and Information

Optional

Cours

e

 

 

 

 

 

s

Theoretical

Courses

Bayesian Statistics

 

2

 

36

2

School of Statistics and Information

Statistical Computing

 

2

 

36

2

School of Statistics and Information

Financial Mathematics  

 

2

 

36

2

School of Statistics and Information

Actuarial mathematics of life insurance

 

 

2

36

2

School of Statistics and Information

Actuarial Model

 

 

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

Linguistic

Courses

Survival Analysis 

 

2

 

36

2

School of Statistics and Information

Spatial Statistics

 

2

 

36

2

School of Statistics and Information

Data Mining

 

3

 

54

3

School of Statistics and Information

Advanced Database Technology

 

3

 

54

3

School of Statistics and Information

Introduction to Algorithms

 

2

 

36

2

School of Statistics and Information

Statistical software(SAS)

 

2

 

36

2

School of Statistics and Information

Risk Management

 

 

2

36

2

School of Statistics and Information

Generalized Linear Model and Mixed Effects Model

 

 

2

36

2

School of Statistics and Information

Analysis of Complex Data

 

 

2

36

2

School of Statistics and Information

Interdisciplinary Courses

(Students are required to take at least one interdisciplinary course for 2 credits.)

International Logistics and Supply Chain Management

 

 

 2

36

2

School of Business

Electronic Commerce

 

 

2

36

2

School of Business

Monographic Study on Marketing Management

 

2

 

36

2

School of Management

Monographic Study on Consumer Behavior

 

 

36

2

School of Management

Financial Econometrics

 

3

 

54

3

School of Finance

Research in Financial Engineering

 

2

 

36

2

School of Finance

Research in Corporate Finance

 

2

 

36

2

School of Finance

Fixed income securities Research

 

 

2

36

2

School of Finance

Research in International Finance

 

 

2

36

2

School of Finance

Investment

 

 

2

36

2

School of Finance

 

Students are required to take at least one cross-specialty course for 2 credits.

Lectures

eight times

 

2

School of Statistics and Information

Social Practice

 

 

 

 

1

School of Statistics and Information

 

 

 

 


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