打算出国留学的学生有很多，但是有很多朋友对留学的相关信息不太了解，本站编辑就为大家整理了哥伦比亚大学统计学的内容，希望对大家有帮助。

1、地处黄金地段的哥伦比亚大学

Columbia University

1255 Amsterdam Avenue (between 121st and 122nd Street)

New York, NY 10027

Phone:212.851.2132

Fax: 212.851.2164

哥伦比亚大学所在的纽约市是国际经济、金融、艺术、传媒之都，联合国总部与各类国际性组织总部所在地，也是全球最具特色的移民城市之一，约有180余个国家与地区的移民在此生活，这一丰富多元的人文社会资源极大地方便了学院的科研活动与学生实习。一方面，因地缘优势，学院承担了大量由联合国与各国际组织所委托进行的科研项目，同时本院学生可极为便利地获得去上述机构进行实习的机会。另一方面，移民城市的种族与民族多样性、流动性及阶层多元化，为学院教员与学生的各类教育研究提供了世界上最大最多元的教育研究与实验土壤，为各类研究提供了便利。此外，纽约市还为学生提供了大量非正式教育机会，学生们可广泛利用各类戏剧院、博物馆、音乐会、讲座或大型会议等获得学习机会。有一句话形象的点出了这一点：“哥大的学生在华尔街学经济、金融，在联合国总部学政治，在百老汇看戏剧。

虽说哥大地理位置在黑人区夹缝中生存，不过并不能阻止一届又一届学子魔鬼般前仆后继申请的步伐。

2、哥伦比亚大学官方对统计学的定义

The Statistics major is an appropriate background for graduate work, including doctoral studies in statistics, social science, public health, genetics, health policy, epidemiology, marketing, opinion polling, economics, finance and banking, government, drug development, and insurance. Statistics is the art and science of study design and data analysis. Probability theory is the mathematical foundation for the study of statistical methods and for the modeling of random phenomena.

统计学常被运用的领域有：社会科学(人口统计学)，公共卫生(近年来流行的生物统计学，流行病与统计学，健康卫生政策制定)，基因处理(高维数据)，市场调查，经济学，金融学，制药，保险。

统计学和随机现象模型分析要求很强的概率论背景，拥有优异的概率论成绩会对申请起到很大的帮助。

3、统计博士项目/硕士项目的就业方向？

The Ph.D. program prepares students for research careers in probability and statistics in academia and industry. The M.A. in Statistics program prepares students for careers in finance, healthcare analytics, environmental science, and other data-intensive fields.

博士：概率论和统计的学术研究或业界研究(研究所等);

硕士：金融，医疗分析，环境科学，及其他需要大量数据分析的行业。

4、哥大统计硕士项目共分为6个分支，下述为详细介绍与分析。

(1)M.S. IDSE：数据科学硕士

http://stat.columbia.edu/programs/m-a-programs/ma-idse/

The MS in Data Sciences will offer students an in depth education experience to focus on data science as it pertains to their unique interests. Students will be interacting with diverse faculty members and students, given the opportunity to conduct research opportunities, included in a capstone project course, and available for industry interaction.

Students will be given the opportunity to select an elective track which incorporates the six centers (Cyber-security Center, Financial and Business Analytics Center, Foundations of Data Science Center, Health Analytics Center, New Media Center; Smart Cities Center) within the Institute as well as an Entrepreneurship track. This allows students to hone in on their particular interests and skill sets.

该项目为学生提供与他们兴趣相关的数据科学教学，既有机会做科研又可以与业界合作。

为提高学生对统计学的实践应用能力，学生有机会从6个研究中心中选择一个方向进行具体实践——网络安全中心，金融商业分析中心，基金数据科学中心，健康分析中心，新媒体中心，Smart Cities(见注解)中心;以及企业方向。

注解：smart cities就是运用信息和通信技术手段感测、分析、整合城市运行核心系统的各项关键信息，从而对包括民生、环保、公共安全、城市服务、工商业活动在内的各种需求做出智能响应。其实质是利用先进的信息技术，实现城市智慧式管理和运行，进而为城市中的人创造更美好的生活，促进城市的和谐、可持续成长。

(2)M.A. program in Quantitative Methods in the Social Sciences (QMSS)：社科计量方法硕士

http://www.qmss.columbia.edu/

It is designed for students with a background in social sciences orquantitative methods who are interested in deepening their analytical skills and broadening their knowledge of the social sciences.

Quantitative Methods in the Social Sciences(QMSS) is an innovative, flexible, interdisciplinary social science Master ofArts degree program at Columbia University that focuseson quantitative research techniques and strategies. The program integrates theperspectives and research methods of six social science disciplines: Economics, History, Political Science, Psychology, Sociology, and Statistics.

QMSS provides students with rigorous training in quantitative research, with an emphasis on written and oral communication about research techniques and findings. These skillsprepare QMSS graduates to enter (or further) an analytical or research career orto continue their education in a PhD program.

QMSS项目旨在培养学生运用数量方法去解决在商业、政府、非盈利机构中出现的问题，并为申请社科博士项目的学生打下基础。设置该专业的目标对象主要是那些需要增强分析能力以及需要扩展社科认知的童鞋，当然QMSS也会教会你很多东东，比如说数量研究啊，科研中写作交流能力之类的。

(3) M.A. in Statistics Hybrid Online/On Campus Program：网络和校园课程混合型硕士

http://stat.columbia.edu/programs/m-a-programs/ma-statistics-hybrid-onlineon-campus-program/

The Department of Statistics has developed a program that will offer select courses in its renowned M.A. program in a partially online format. While the degree requirements for the Hybrid Online/On-Campus Program are similar to those of the regular On-Campus Program, four core courses will be delivered entirely online in the first fall semester offering students more flexibility in completing the MA degree. The remaining courses will then be completed on campus. The MA Hybrid students are only Hybrid in the first semester of the program and then are completely integrated into the resident program after the first semester. The diploma and degree is identical for initial Hybrid and non-Hybrid entry students.

The program is designed to help students establish a deep foundational knowledge of statistical methods. The first-year coursework will give students the proper background and training in modern probability, statistics, and applied statistics in a systematic fashion and prepare them for the more advanced courses offered subsequently. The initial four courses will be conducted exclusively online through our innovative learning management system. In general, most students in the Hybrid Program take the entire suite of 4 courses in semester one. Please note that online courses will not be offered again until the following fall.

何为混合型硕士项目，官方解释是，授课方式包含全网络课程和在校课程。为了让学生更好地适应环境，更自由的安排学习时间，第一学期的四门课都是网络课程，但是接下来的课程和别的项目一样，需要在校园内完成。

那么混合型的授课方式是否具有高的可靠程度呢?据官网说明：混合型与非混合型项目的学位证书和毕业证一致，设立该项目主要是考虑到修读统计学专业的很多学生仍有工作的需要，因此为其设定了一年的缓冲时间。

(4) M.S. in Actuarial Science：精算学硕士

http://stat.columbia.edu/programs/m-a-programs/programms-actuarial-science/

The program grounds students in the theory and methods used by actuaries at the same time that it prepares them to take SOA Exams P, FM, MLC, MFE, and C or CAS Exams 1, 2, 3L, 3F and 4.

The program is appropriate for students with a strong record of academic achievement in mathematics, statistics, or economics. Students should enter with a knowledge of elementary economics, linear algebra, and multivariate calculus.

这个项目的名称就会引来无数学子竞争申请。该项目主要强调理论和方法，并在攻读过程中带你考精算师的等级证书。

申请该项目的学生需要有基础的经济学，线性代数，多元微积分背景。

(5) M.A. in Mathematical Finance：这就是传说中的金融数学

http://www.math.columbia.edu/mafn/

The Department of Mathematics jointly with Department of Statistics at Columbia University offers a track of its Master of Arts in Mathematics with specialization in the Mathematics of Finance. The program draws on the diverse strengths of Columbia in stochastic processes, numerical methods, and Finance.

The program is oriented towards students with degrees in the Mathematics, Physics, and Engineering Science who wish to develop strong analytic skill in preparation for a career in finance.

这是数学学院和统计学院合作开设的项目，项目强调随机过程，数值分析等在金融领域的应用。该项目主要面向以数学、物理、工程学为背景并且想将其应用于金融领域的学生。

(6) M.A. in Statistics：统计学硕士

http://stat.columbia.edu/programs/m-a-programs/ma-statistics/

The department offers an M.A. program designed for students preparing for professional positions or for doctoral programs in statistics and other quantitative based fields. The program may be taken either full-time or part-time. Most courses, and all required courses in the program, have at least one evening section in order to accommodate working students. This program is designed to be completed in three semesters (Fall/Spring Year 1 and Fall of Year 2). Students may also opt to take summer classes. Part-time domestic students may take two to three courses per semester and must complete the program in a four year time period.

此专业是哥大统计系下属申请人数最多的专业，也是最具争议的专业。在前述5个专业存在的情况下，为何还会有该项目的存在?官网指明，这个项目主要适合想要继续在统计学学术前沿领域深造但是并未确立具体研究领域或研究方向的学生，类似于人们所讲的general statistics.该项目也是哥大统计系下每年招收人数最多的项目。

5、 PH.D in Statistics：统计学博士

http://stat.columbia.edu/programs/ph-d-program/

PH.D. students are admitted only in September. Admissions decisions are made in late February of each year for the Fall semester. A student admitted to the Ph.D. program normally has a background in linear algebra and real analysis, and has taken a few courses in statistics and probability. Familiarity with computing and programming is desirable. Students who are quantitatively trained or have substantial background/experience in other scientific disciplines are also encouraged to apply for admission. Prospective Ph.D. students must take the Graduate Record Examination (GRE) general test. The GRE Advanced Subject Test in Mathematics is also highly recommended. The deadline for application (Ph.D. program) is January 6.

哥伦比亚大学的统计学博士项目是很难申请的。对于申请者，不仅要求很强的数学分析和代数学背景，实变函数，概率论，编程和计算机语言的运用也必不可少。并且申请人需要具备GRE数学专业考试的成绩。

注: 申请博士的学生，上策留学在这里建议大家如果时间允许，争取考出一份理想的GRE数学单项成绩，部分学校在申请时，要求学生具有GRE SUB成绩（详情请咨询上策留学）。

哥大的博士项目，申请的截止日期为1月6日。

注：美国大多数学校的博士和硕士申请截止日期不同，博士的申请截止日期大多数聚集在11月30日，12月8日，12月30日和第二年的1月15日;而硕士的申请截止日期主要集中在第二年的2月-5月。因此确定申请博士的学生需要提早安排申请计划。（详细的申请要求和具体学校的申请截止日期请咨询上策留学）

6、哥大统计学院下属的课程设置

以M.S.IDSE(数据科学硕士)的课程设置为例，大家可以发现哥大统计学院下属的课程设置具有极高的价值性：课程种类多，并且涉及各个领域。并且哥大为学生提供了丰富的选修课程，使学生不局限于他所在的项目，一个项目的学生可以选择其余项目开设的课程，并且可以有意识的选择自己感兴趣的方向。

Core Courses(核心/必修课程)：

Probability

概率论

A calculus-based introduction to probability theory. Topics coveredinclude random variables, conditional probability, expectation, independence,Bayes’ rule, important distributions, joint distributions, moment generatingfunctions, central limit theorem, laws of large numbers and Markov’sinequality.

Algorithms for Data Science

数据科学的算法

Methods for organizing data, e.g. hashing,trees, queues, lists, priority queues. Streaming algorithms for computing statistics on the data. Sorting and searching. Basic graph models and algorithms for searching, shortest paths, and matching. Dynamic programming.Linear and convex programming. Floating point arithmetic, stability of numerical algorithms, Eigenvalues, singular values, PCA, gradient descent,stochastic gradient descent, and block coordinate descent. Conjugate gradient, Newton and quasi-Newtonmethods. Large scale applications from signal processing, collaborativefiltering, recommendations systems, etc.

Statistical Inference and Modeling

统计推断和建模

Course covers fundamentals of statisticalinference and testing, and gives an introduction to statistical modeling.

The first half of the course will be focused on inference and testing, covering topics such as maximum likelihood estimates, hypothesis testing, likelihoodratio test, Bayesian inference, etc.

The second half of the course will provide introduction to statistical modeling via introductory lectures on linear regression models, generalized linear regression models, nonparametric regression, and statistical computing.

Throughout the course, real-data examples will be used in lecture discussion and homework problems.

Computer Systems for Data Science

计算机系统数据科学

An introduction to computer architectureand distributed systems with an emphasis on warehouse scale computing systems. Topics will include fundamental tradeoffs in computer systems, hardware and software techniques for exploiting instruction-level parallelism, data-level parallelism and task level parallelism, scheduling, caching, prefetching, network and memory architecture, latency and throughput optimizations,specialization, and an introduction to programming data center computers.

Machine Learning for Data Science

机器学习

An introduction to machine learning, with an emphasis on data science. Topics will include least squares methods,Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesianinference, mixture models, the EM algorithm, graphical models, hidden Markovmodels, support vector machines, and kernel methods. Part of the course will be focused on methods and problems relevant to big data problems.

Exploratory Data Analysis and Visualization

探索性数据分析和可视化

This class introduces the data processingand algorithmic skills, as well as design principles necessary to explore andpresent datasets computationally and visually. These include command linetools, the use of state-of-the art languages and software, an algorithmicunderstanding of how to work with a large datasets (including parallelism andthe map-reduce framework), interactive visualizations, exploratory dataanalysis as a means to generate and test hypotheses, as well as basics of dataexploration and visualization.

Data Science Capstone & Ethics

数据处理及伦理

This course provides a unique opportunityfor students in the MS in Data Science program to apply their knowledge of the foundations, theory and methods of data science to address data science problems in industry, government and the non-profit sector.

The course activities focus on a semester-length data science project sponsored by a local organization. The project synthesizes the statistical, computational,engineering challenges and social issues involved in solving complex real-world problems.

Electives(选修课程)：

In addition to the core courses, students must also complete elective courses approved by their FacultyAdviser. For the electives, at least three must be selected from the Statistics Department, upon approval by the Faculty Adviser.

Possible Electives by Area of Interest:Students may choose courses that are recommended based upon area of interest.These electives are not required to take but are simply helpful recommendations.

Finance

Data Science

Pharmaceutical industry

Public Health

Actuarial Science

Environmental Science

Insurance industry

PhD

学生可选修金融、数据科学、制药业、公共卫生、精算科学、环境科学、保险业方面的课程;如果有意向继续攻读Ph.D学位的学生，也可以利用选修课的机会，学习Ph.D学生的必修课程。

7、Placement of students at Columbia University Department of Statistics 哥伦比亚大学统计学院近10年毕业生去向

2006

Boston University

SAC Capital Management

BlackRock

NPS Pharmaceuticals

National Universityof Singapore

National Insitutes of Health

2007

Credit Suisse

ETS

2008

Duke University

Forrest Lab

Barclays, London

Moodys

2009

University of Santa Barbara

Stanford University

2010

John Hopkins University

Novantis Pharmaceuticals

Barclays

Pragma Securities, INC

Google

Chinese Universityof Hong Kong

University of Southern California

Baruch College

Fannie Mae

2011

L’universite d’Evory vak d’Essonne

University of Washingto, Seattle

University of Oxford

Gilead Sciences, Inc

JP Morgan

Skill in Games, LLC

2012

Google

Knight Capital

Cash Dynamic OpportunityInvestment

University of Alberta

2013

Promontory Financial Group

Goldman & Sachs

University of Minnesota

Baruch College

Google

University of Vienna

2014

New York University

Bank of America

由于哥伦比亚大学统计学院每年招收学生的人数较多，中国留学生占总学生的比例较大，哥大统计系在留学生中具有较大的争议。但是我们在这里想要告诉大家：

当我们选择学校时，最重要的是它开设的课程能否帮助我们快速掌握工作所需要的知识和技巧，能否向我们提供珍贵的实习和科研机会，是否具有强大的师资力量，学生的毕业去向是否理想，是否具有强大的校友资源。

不仅仅是哥伦比亚大学，我们熟悉的统计强校：密歇根大学安娜堡分校，康奈尔大学，加州大学伯克利分校，卡耐基梅隆大学等，中国学生都占有十分高的比例。

因此，不要因为外界的传言，不加深入分析地否定一个可能会十分适合自己并且能够助自己实现人生理想的学校。

以上就是哥伦比亚大学统计学的全部内容。

相关推荐：

美国哥伦比亚大学gpa要求

哥伦比亚大学gre要求全解

美国哥伦比亚大学不同专业gre分数要求