Graduate Catalog
2017-2018
 
Policies, Procedures, Academic Programs
Statistics
College of Science
Academics and agricultural administration; completed February 1940. Cost $206,000; 39,280 sq. ft, Originally known as New Agricultural Hall. Named after Thomas Barksdale Hutcheson (1882-1950) was Head of the Department of Agronomy from 1914 to 1945 and Dean of the School of Agriculture from 1946 to 1950. He lived in the dairy barn at Virginia Agricultural and Mechanical College and Polytechnic Institute (Virginia Tech), working his way through college by milking cows.
250 Drillfield Drive 405A Hutcheson Hall, Mail Code:0439 Blacksburg VA 24061
Hutcheson Hall
Degree(s) Offered:
• MS
MS Degree in Statistics
Minimum GPA: 3.0
Offered In:
Blacksburg
• PhD
PhD Degree in Statistics
Minimum GPA: 3.0
Offered In:
Blacksburg
Web Resource(s):
Phone Number(s):
540/231-5630
Application Deadlines:
Fall: Jan 15
Directions
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Hutcheson Hall

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Department Head : Ronald Fricker
Graduate Program Director : Marco Ferreira (Director of Graduate Programs in Statistics)
Professors: Ronald Fricker; Robert Gramacy; David Higdon (National Capital Region); Ina Hoeschele; Sallie Keller (National Capital Region); John Morgan; Eric Smith; Gordon Vining; William Woodall
Associate Professors: Xinwei Deng; Pang Du; Marco Ferreira; Feng Guo; Yili Hong; Leanna House; Inyoung Kim; Scott Leman; George Terrell
Assistant Professors: Christopher Franck; Leah Johnson; Shyam Ranganathan; Srijan Sengupta; Xiaowei Wu; Hongxiao Zhu
Assistant Professor of Practice: Anne Driscoll; Jane Robertson Evia
Research Assistant Professors: Allison Tegge

Statistics Introduction

Founded in 1949, the Department of Statistics at Virginia Tech is the third oldest in the nation. Our program specializes in training students in statistical theory balanced with extensive applications including practical experience via the Statistical Applications and Innovations Group (SAIG). Over 875 master's degrees and 368 doctoral degrees have been awarded by the department. The 18-month master's program is a model of the time-efficient education of statisticians. The doctoral program includes specialized tracks in traditional and industrial statistics, bioinformatics, computational statistics (data analytics), and environmetrics.
Offered In (Blacksburg)

Degree Requirements

Minimum GPA: 3.0
Institution code: 5859
Testing Requirements:
  • TOEFL
    • Paper
      • 550.0
    • Computer
      • 213.0
    • iBT
      • 80.0
  • GRE
    • General Test
      • Verbal : 150.0
      • Quantitative : 160.0
      • Analytical : 3.0

The M.S. plan of study requires 34 semester hours of work, of which 32 semester hours must be taken within the department. Additional courses rounding out a plan of study may be taken at the graduate level in applied or theoretical statistics, mathematics, or in approved areas of application. Each student must pass a qualifying examination after completing the core courses and a final oral examination after completing the plan of study.

The Ph.D. plan of study requires a minimum of 90 semester hours of work beyond the baccalaureate, including at least 58 semester hours of coursework and at least 30 semester hours of research toward the dissertation. In addition to the core courses for the M.S. (or equivalent courses if a student enters the program with advanced standing from another university), required courses for the Ph.D. are Advanced Topics in Statistical Inference and three other Ph.D. level courses from approved lists of courses, which vary by track. Each candidate for the Ph.D. must pass the qualifying examination at the Ph.D. level.

Flexibility is provided to the graduate program through five Ph.D. concentrations or tracks, which include the Traditional Track, the Bioinformatics Track, the Computational Track, the Environmental Track, and
the Industrial Track. The Traditional Track encompasses the general pursuit of research in statistical theory and methods, allowing considerable freedom in choice of coursework within and outside the department. The Bioinformatics, Computational, Environmental, and Industrial Tracks offer more specialized statistical training geared toward application areas in which the department has particular expertise. In accord with their specialized nature, these four tracks are more stringent in requirements for relevant coursework than the Traditional Track. An option in Bioinformatics is also available.

Offered In (Blacksburg)

Degree Requirements

Minimum GPA: 3.0
Institution code: 5859
Testing Requirements:
  • TOEFL
    • Paper
      • 550.0
    • Computer
      • 213.0
    • iBT
      • 80.0
  • GRE
    • General Test
      • Verbal : 150.0
      • Quantitative : 160.0
      • Analytical : 3.0

The M.S. plan of study requires 35 semester hours of work, of which 32 semester hours must be taken within the department. Additional courses rounding out a plan of study may be taken at the graduate level in applied or theoretical statistics, mathematics, or in approved areas of application. Each student must pass a qualifying examination after completing the core courses and a final oral examination after completing the plan of study.

The Ph.D. plan of study requires a minimum of 90 semester hours of work beyond the baccalaureate, including at least 59 semester hours of coursework and at least 30 semester hours of research toward the dissertation. In addition to the core courses for the M.S. (or equivalent courses if a student enters the program with advanced standing from another university), required courses for the Ph.D. are Advanced Topics in Statistical Inference and three other Ph.D. level courses from approved lists of courses, which vary by track. Each candidate for the Ph.D. must pass the qualifying examination at the Ph.D. level.

Flexibility is provided to the graduate program through five Ph.D. concentrations or tracks, which include the Traditional Track, the Bioinformatics Track, the Computational Track, the Environmental Track, and
the Industrial Track. The Traditional Track encompasses the general pursuit of research in statistical theory and methods, allowing considerable freedom in choice of coursework within and outside the department. The Bioinformatics, Computational, Environmental, and Industrial Tracks offer more specialized statistical training geared toward application areas in which the department has particular expertise. In accord with their specialized nature, these four tracks are more stringent in requirements for relevant coursework than the Traditional Track. An option in Bioinformatics is also available.

Statistics Facilities Introduction

Through the Statistical Applications and Innovations Group, students in cooperation with faculty members become involved in on-campus collaboration activities. M.S. students are required to participate in statistical collaboration within the Statistical Applications and Innovations Group (SAIG) for at least one semester and Ph.D. students for at least three semesters. The department has several laboratories housing state-of-the-art Linux and PC networks. Students have access to these for collaboration, course work, and research. Students gain extensive experience with modern statistical software for experimental design, data management and analysis, and computer programming for statistical purposes.
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