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«The University of Connecticut Department of Statistics Graduate Program Founded in 1963, the Department is one of the major statistics departments in ...»

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The University of Connecticut

Department of Statistics

Graduate Program

Founded in 1963, the Department is one of the major statistics departments in the Northeast and has

national and international recognition in both teaching and research. Core faculty have research interests in major

areas of probability and statistics, spanning virtually all modern areas of statistical applications.

Graduate education has been a traditional strength of the Department with over 60 Ph.D. and 140 M.S.

degrees awarded in the last 10 years. The graduate program balances theory, methods and applications, including a solid foundation in mathematical statistics, probability theory, statistical methodology and modeling, data analysis, and computational statistics. Elective courses are regularly given in active areas of research with emphasis on modern and model based statistical methodology.

Graduates of the program promptly move into attractive positions in academics, government, and industry, specific areas including biology, medicine, business, economics, engineering, and the social sciences.

Programs of Study The Department of Statistics offers programs leading to M.S. in Statistics, Professional M.S. in Biostatistics and Ph.D. degrees. All programs include training in statistical application and theory, and give students sufficient flexibility to pursue their special interests as well as time to take courses in other departments at UCONN.

The M.S. program in statistics requires 8-10 courses, depending on a student’s previous academic record.

While it is possible to complete the M.S. degree within a year, most students will need three or four semesters. The core courses of the program cover mathematical statistics, linear models, design of experiments, and applied statistics; please see the description of the M.S. program for more detail. Students are encouraged to participate in statistical consulting projects done by members of the Department.

The professional M.S. program in Biostatistics requires 10 courses, which will focus on practical skills that are sought after in health related fields, including pharmaceutical sciences and genomics. Students completing this program successfully will acquire expertise in topics including statistical inference, linear regression, analysis of variance, design and analysis of clinical trials and epidemiological studies, programming in SAS and R, and consulting. Please see the description of the M.S. Biostatistics program for more detail.

Both MS programs will give you a solid foundation in theory and methods of statistics, so you also will be able to find a job in industry, or to continue your study as a PhD candidate.

The Ph.D. program emphasizes development of the ability to generate novel results in statistical methods, statistical theory, or probability. The course work typically consists of at least sixteen graduate level courses that cover a wide range of topics, including mathematical statistics, linear models, statistical inference, applied statistics, real analysis, and probability. After completing the necessary course work and a sequence of examinations, a Ph.D.

candidate must complete a dissertation that makes an original contribution to the field of statistics or probability.

The dissertation may be predominantly development of novel statistical methodology for an area of application. For more detail, please see the description of the Ph.D. program for more detail.

Research Facilities

Research and teaching Labs for the Department of Statistics are housed in the Philip E. Austin Building. The Department has a teaching computer lab and a research computer lab. The Department has as 21 seat research lab with a mix of Intel-based Linux and Windows systems dedicated to large scale numerical computing and statistical simulation. The Department also has a Linux based computer cluster with over 300 CPU’s for computing intensive statistical research. A large software base is now available in either the PCs or the Linux workstations in both labs, which includes SAS, S-Plus, SPSS, GLIM, MINITAB, Mathematica, Maple, IMSL (Fortran and C), R, OpenBUGS, as well as other packages and languages. IMSL (Fortran and C) and R are also available in the department Linux cluster.

Both the research lab and computing cluster are accessible to PhD students, visiting scholars, and faculty members.

The teaching lab exclusively features Windows machines with similar software bundles and is used for both graduate and undergraduate computing classes. When not in use for teaching, the lab is open to all students with teaching assistants on duty to serve as tutors.

The Department’s computers are managed and maintained by four lab managers, a Linux quarter time operations manager and a PC quarter time operations manager from the office of the Dean of the College of Liberal Arts and Sciences, and a student Linux cluster manager and a student Webmaster. The computer management team maintains, installs, and upgrades the operating systems and software, and they also provide the service of weekly tape-backing up as well as daily trouble-shooting of system problems.

Financial Aid

Graduate teaching and research assistantship and fellowship-assistantship combinations are available (to qualified students in the Ph.D. program) covering tuition and health benefits with a stipend of $20,965-$24,526 for a 100% Graduate Assistant for the academic year 2015-2016. Some internships and financial aid are available in the summer. Students with full aid generally take three courses a semester. Those with a fellowship-assistantship may take four courses. Outstanding students may be awarded University predoctoral fellowships. Advanced students are considered for research assistantship.

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Please refer to the Graduate School website for information on tuition, www.grad.uconn.edu/tuition and Residential Life for information on housing, www.reslife.uconn.edu.

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There are close to 120 graduate students in the department, approximately 75 working towards an M.S.

degree and 43 for the Ph.D. degree. The department has been granting 6-7 Ph.D. degrees a year. All graduate students and faculty have office space within the department, creating an open, informal environment. Of the 33 Ph.D. recipients in the last five years, 11 have academic tenure track positions, 20 in industry and 1 in government.

The M.S. recipients have positions with the government, industry and business, and academic research centers. As predicted by the National Science Foundation, employment opportunities for persons with degrees in statistics continue to be excellent.

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The University of Connecticut’s main campus is in northeastern Connecticut, 25 miles from Hartford, in an attractive rural area. It is about 1-1/2 hours by car from Boston and 3 hours from New York City.

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The University of Connecticut, which celebrated its centennial in 1981, is the state of Connecticut’s landgrant institution. It has about 30,000 students, including more than 8,000 in graduate study. Its substantial, but not overwhelming, size allows the University to offer a broad curriculum and an excellent program of concerts, plays, and other cultural events.

The Department of Statistics was founded in 1963. Its faculty members conduct an active and prolific research program in which students are involved as soon as possible.

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Applicants who wish to be considered for financial aid should apply for fall admission and must submit a complete application to the University by February 1. Please note that financial aid is only available for Ph.D.

applicants. Applicants not seeking financial aid can apply until June 1 for fall admission and until October 1 for spring admission, however, spring admission is typically reserved for current UConn students.

Most of our students come from undergraduate Mathematics or Statistics majors. Persons with degrees in fields other than Statistics and Mathematics are encouraged to apply.

While there are no official course requirements for admission, a level of mathematical sophistication and statistical knowledge is necessary for acceptable progress. At the minimum, this amounts to (1) three semesters of calculus, including one semester of multivariate calculus (2) one semester of linear algebra, and (3) two semesters of undergraduate statistics. Course work to remedy deficiencies can be taken while in the program.

The following are basic criteria for the evaluation of an application:

GRE scores: Taken within 5 years with a verbal score above the median and a quantitative score ranked in the top twenty five percent for financial support. Please note that in August 2011, there were substantial changes in the GRE general test. GRE scores from the old exam format (but no older than 5 years) will still be accepted. For more information, go to the official GRE website at www.ets.org/gre.

English Proficiency: If you are not a native speaker of English, you must submit evidence of your proficiency in the English language. You may use the (no more than 2 years old) results from either one of the two standardized tests to satisfy this requirement. If you submit results from the Test of English as a Foreign Language (http://www.ets.org/toefl/) (TOEFL), you need a minimum overall score of 550 for the paper-based test, or 79 for the internet-based test. If you submit results from the International English Language Testing System (http://www.ielts.org) (IELTS), you need an average overall band score of at least 6.5. Only the scores from the Academic Module, not the General Training Module, are applicable. If you submit results from the Person Test of English (PTE) we require an overall score of 53. Applicants who have a degree from a college in the U.S. can have the score waived, however, for Ph.D. applicants who want to be considered for a teaching assistantship, TOEFL scores are required.

Transcripts: You must submit all applicable, official transcripts (undergraduate & graduate). Your

transcript(s) must meet the following criteria:

-A cumulative grade-point average of 3.0 for your entire undergraduate career or

-A grade-point average of at least 3.0 for your last two undergraduate years or

-Exceptional work in your entire final undergraduate career (3.5 or better) or

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For students entering the program after a Bachelors Degree, typically 16 to 18 courses are required. An individual plan of study is developed by the student and his or her Advisory Committee.

Knowledge of a sequence of core courses is required for all Ph.D. students. These courses are 5585-5685 (Mathematical Statistics), 5505-5605 (Applied Statistics), 5725, 6694 (Linear Models), 6315, 6515 (Theory of Statistics), 6325-6894 (Measure Theory and Probability Theory), 5515 (Design of Experiments), giving a total of 33 credits for core courses. Additional credits can be earned from the list of elective courses.

In general, Ph.D. students are required to elect 1 – 2 courses from other departments. However, it is sufficient to take one graduate level course from the Department of Mathematics. Ph.D. students are also encouraged to take courses in Computer Science as well as in application areas such as Biology or Economics. The elected course(s) must be approved by the major advisor of a student. Under certain circumstances, a major advisor can exempt his/her student from the above requirement, if the student has had internships or RA’s in interdisciplinary areas. The Department has no requirement on foreign languages.

The first formal departmental requirement for the Ph.D. program is successfully passing the Ph.D. Qualifying Examination which is a written test of certain basic courses to the program. The next requirement is passing of the General Examination which is given as an oral test and covers aspects of Applied Statistics, Linear Models, Probability Theory and Statistics. The preparation of a dissertation then follows which must present an original contribution to the general area of Statistics and/or Probability. The final requirement of the program is a defense of the Ph.D. dissertation before an audience of interested members of the department.

The Department expects every Ph.D. student to strive to finish his or her study within 4 years. For students arriving without a M.S. degree in Mathematics or Statistics, the Department may provide up to 5 years of financial support. For those arriving with such a degree, the Department may provide up to 4 years of financial support.


In order to receive continuous support, Ph.D. students with financial support should maintain suitable course load. Each should take at least 3 courses in each semester until taking the Ph.D. Qualifying Examination. For students arriving with a Bachelor’s Degree and receiving financial support from the Department, we propose the

following timetable for these examinations:

1. Ph.D. Qualifying Examination: within 3 semesters from start of program.

2. General Examination: within 6 semesters from start of program.

3. Ph.D. Thesis Defense: no later than 5 years from start of program.

In order for a student currently enrolled in our M.S. program to switch to the Ph.D. program or to be considered for financial support, he or she must first pass both parts of the Ph.D. Qualifying Exam at Ph.D. level.

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The M.S. program emphasizes applied statistics and requires students to take at least one course in areas of application. The plan of study for this degree may be formulated with related work in almost any area, e.g., Biology, Business, Economics, Nutrition, and Psychology to name a few.

Individuals with a Bachelor’s degree in any major, with a background in mathematics and statistics are encouraged to apply. In general, three semesters of full time study, normally four courses per semester, are required to complete the MS degree, although it is possible for a student with a strong background to finish in one year. A student holding an assistantship, or who is otherwise prevented from carrying a full load of graduate work, generally requires an additional semester to finish.

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