美國統(tǒng)計學(xué)專業(yè)申請解析及院校意見

統(tǒng)計屬于應(yīng)用數(shù)學(xué)領(lǐng)域，統(tǒng)計學(xué)是通過搜索、整理、分析、描述數(shù)據(jù)等手段，以達(dá)到推斷所測對象的本質(zhì)，甚至預(yù)測對象未來的一門綜合性科學(xué)。其中用到了大量的數(shù)學(xué)及其它學(xué)科的專業(yè)知識，它的使用范圍幾乎覆蓋了社會科學(xué)和自然科學(xué)的各個領(lǐng)域。所謂的大數(shù)據(jù)就是各行各業(yè)工作中所需求的數(shù)據(jù)經(jīng)過統(tǒng)計分析處理后，我們才可真正的獲得有價值的數(shù)據(jù)。

從美國的開設(shè)統(tǒng)計學(xué)專業(yè)的學(xué)校來看，統(tǒng)計學(xué)大致可以分為兩類，一類是偏向于理論研究的，另一類是偏向于實際應(yīng)用的。前者主要包括統(tǒng)計系或者數(shù)學(xué)系下統(tǒng)計學(xué)，后者包含的方面就非常的廣泛了，包括目前非常熱門的生物統(tǒng)計，還有經(jīng)濟統(tǒng)計、以及社會統(tǒng)計學(xué)等。每個方向未來的發(fā)展也是不同的。

理論方面包括；樣本設(shè)計、數(shù)據(jù)挖掘、隨即過程、建立統(tǒng)計模型、模型的選擇、時間序列、非參數(shù)統(tǒng)計方法、蒙特卡羅法、生存分析、空間統(tǒng)計、貝葉斯推論、各種經(jīng)典的統(tǒng)計模型的學(xué)習(xí)、各種概率論理論等。

應(yīng)用方面包括：

生物統(tǒng)計、環(huán)境統(tǒng)計、金融統(tǒng)計、經(jīng)濟統(tǒng)計、遺傳統(tǒng)計、農(nóng)業(yè)統(tǒng)計等等。這些是統(tǒng)計在其他領(lǐng)域的應(yīng)用而形成的研究分支。

學(xué)位設(shè)置：

MS學(xué)位，即Master of Science in Statistics，也有的學(xué)校稱之Master of Science in Applied Statistics。

MS學(xué)位通常為兩年制，它更加側(cè)重于學(xué)術(shù)研究，畢業(yè)后可以選擇就業(yè)也可以選擇繼續(xù)攻讀Ph.D學(xué)位。

部分院校會設(shè)置MA學(xué)位，旨在培養(yǎng)學(xué)生短期的統(tǒng)計技能，為將來的就業(yè)做準(zhǔn)備，如果打算繼續(xù)攻讀博士學(xué)位的學(xué)生一般不建議考慮該學(xué)位。還有一些院校會有MAS學(xué)位，即Master of Applied Statistics），主要是強調(diào)統(tǒng)計的應(yīng)用，傾向于畢業(yè)直接找工作的學(xué)生，與MA學(xué)位相似。

因此，申請者在申請具體學(xué)位的時候，要結(jié)合自身的發(fā)展需求，仔細(xì)鉆研目標(biāo)院校的學(xué)位設(shè)置，因其側(cè)重點的不同，需要學(xué)生做出合理的學(xué)位選擇，這無疑是申請成功的關(guān)鍵點。

申請背景：

1、嚴(yán)格要求數(shù)學(xué)或者統(tǒng)計專業(yè)背景比如University of Washington華盛頓大學(xué)（統(tǒng)計專業(yè)排名第三），University of Southern California南加州大學(xué)等。

2、具備數(shù)學(xué)或者統(tǒng)計相關(guān)本科專業(yè)知識的任何專業(yè)，其中通常會要求修過一定學(xué)分的高等數(shù)學(xué)課程。比如微積分，線性代數(shù)，概率論與數(shù)理統(tǒng)計等。比如University of California-Los Angeles加州洛杉磯大學(xué)。

美國TOP20統(tǒng)計學(xué)專業(yè)院校推薦：

1 University of Chicago

MS in Statistics

The Department of Statistics offers an exciting and revamped graduate program that prepares students for cutting-edge interdisciplinary research in a wide variety of fields. The field of statistics has become a core component of research in the biological, physical, and social sciences, as well as in traditional computer science domains such as artificial intelligence. In light of this, the Department of Statistics is currently undergoing a major expansion of approximately ten new faculty into fields of Computational and Applied Mathematics. The massive increase in the data acquired, through scientific measurement on one hand and through web-based collection on the other, makes the development of statistical analysis and prediction methodologies more relevant than ever. Our graduate program aims to prepare students to address these issues through rigorous training in theory, methodology, and applications of statistics; rigorous training in scientific computation; and research projects in core methodology of statistics and computation as well as in a wide variety of interdisciplinary fields.

The Department of Statistics offers two tracks of graduate study, one leading to the Master of Science (M.S.) degree, the other to the Doctorate of Philosophy (Ph.D.). The M.S. degree is a professional degree. Students who receive this degree are prepared for nonacademic careers in which the use of advanced statistical and computational methods is of central importance. The program also prepares students for possible further graduate study.

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2 Columbia University

MA in Statistics

The Department of Statistics offers two renowned M.A. programs designed to prepare students for professional positions or doctoral programs in statistics and other quantitative-based fields. One is a traditional On-Campus MA program.? The other is a Hybrid Online/On-Campus Program, in a partially online format. Both programs may be completed full or part-time. Full-time students typically complete three semesters – fall and spring of Year 1 and fall of Year 2. Part-time domestic students must take a minimum of two courses per semester and complete the program within four years. Summer courses are also available.?

While the degree requirements for the Hybrid Online/On-Campus Program are similar to those of the regular On-Campus Program, four core courses are delivered online in the first fall semester offering students more flexibility in completing the M.A. degree. The remaining courses will then be completed on campus. The M.A. 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 both the Hybrid and the Non-Hybrid entry students.?

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3 Duke University

Master's in Statistical Science

The Department of Statistical Science admits students to graduate study leading to the Ph.D. degree in Statistical Science and the M.S. degree in Statistical Science.

The Ph.D. in Statistical Science offers thorough preparation in the foundations theory and methods of statistical science--emphasizing modern, stochastic model-based statistical science, and Bayesian and classical approaches to inference, predictive modeling, advanced computational statistics and interdisciplinary applications. Students work with some of the world leaders in research in Bayesian statistics, methodology of statistical science, statistical computing, machine learning and data science, and applications in many fields. Our Ph.D. graduates are strongly recruited for positions in leading academic departments and centers, as well as research positions in business, industry and government.

The M.S. in Statistical Science offers comprehensive education in modern statistical theory, methods and computation. Courses and project work emphasize stochastic model-based approaches to problems of inference and prediction, highlighting Bayesian and machine learning methods. Students develop skills and expertise in modeling complex and potentially massive data and advanced computational methods while gaining exposure to a broad range of application contexts. Our M.S. programs are attractive to students interested in professional careers in industry, business and government, as well as those interested in bridging to Ph.D. studies in statistics and related areas.

A hallmark of all Statistical Science programs is the integration of interdisciplinary applications into teaching and research at all levels, reflecting the department's broad and deep working relationships with many other disciplines (biomedical sciences, business, computational and data sciences, economics and finance, engineering sciences, environmental sciences, genomics and system biology, political and policy sciences, and others). The rich opportunities for students in interdisciplinary statistical research at Duke are complemented by departmental interconnections with industrial research laboratories, government agencies, and commercial and non-profit organizations both nationwide and worldwide.? These lead to opportunities for research travel and regular student internships, as well as follow-on research careers.? In addition, students have opportunities for collaborative research experiences at the US national Statistical and Applied Mathematical Sciences Institute (SAMSI) and National Institute of Statistical Sciences (NISS) on a regular basis.

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4 JHU

Applied Mathematics and Statistics M.A. and M.S.E.

The teaching and research programs of the Department of Applied Mathematics and Statistics span modern applied mathematics.? The department’s curriculum in Probability/Statistics covers probability theory, stochastic processes, and applied and theoretical statistics. Its Operations Research/Optimization program includes continuous and discrete optimization, numerical optimization, network programming, and game theory. Its curriculum in Discrete Mathematics includes combinatorics, graph theory and cryptology and coding.? Its program in Scientific Computing includes computing, numerical analysis, matrix analysis, and mathematical modeling of systems.? The programs of the department together emphasize mathematical reasoning, mathematical modeling and computation, abstraction from the particular, innovative application of mathematics, and development of new methodology.

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5  Cornell University

MPS in Applied Statistics

Our one-year MPS program in?Applied?Statistics readies students for careers in fields where modern data analysis?skills are highly coveted. Built on the three curriculum components of core courses, an in-depth statistical analysis project, and?elective?coursework, our program offers students the option to focus their graduate education in one of two areas: techniques of?applied?statistical analysis or data science, which?includes?high performance computing, databases and scripting.

Equipped with the essential and?foundational understanding of?statistical processes, our students join in a tradition of success, working in global?industries?in diverse fields ranging?from finance to survey analysis to biomedical research.

Option I?focuses on techniques of?Statistical Analysis.

Option II,?Data Science, which along with statistical techniques puts more emphasis on computer science than Option I, for example, high performance computing, databases, middleware, and scripting.

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6 Rice University

MA in Statistics

The research interests of the faculty in the Department of Statistics cover a wide spectrum of topics in applied and theoretical statistics from engineering, natural sciences, business, medicine, and social sciences. Graduate students have the opportunity for rigorous training in computational and theoretical statistics as well as applied research in any of the above disciplines. The general Ph.D. program is flexible, allowing you the opportunity to design a program that interests you, provided that it fits with the strengths of the department.?The M.A. in Statistics is earned as part of working toward the Ph.D.

This summary is intended to give you an idea of the program requirements. The?Rice University General Announcements site is the definitive resource for program requirements.

Master of Arts in Statistics (M.A.)

Candidates for the M.A. degree in statistics must complete 30 semester hours of approved course work and must either complete an original thesis and defend it in a public oral examination or perform satisfactorily on the Ph.D. comprehensive examinations and complete a major project.?

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