statistics

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Admissions
Course Descriptions
MS Program
          PhD Program
              Note: Significant changes, effective Fall 1999, have been made in the requirements for the PhD. Content and numbering of some courses have been changed and new courses added.

              Students planning a career in teaching or research should work for the degree of Doctor of Philosophy. This requires at least three, but more usually four to five, years of full-time graduate work, predicated upon substantial undergraduate mathematical preparation. Research is an important part of the work of doctoral candidates. 

              The philosophy of the Department is that its Ph.D. graduates should be broadly based in statistical theory and practice, and at the same time be able to conduct basic research in some special area of mathematical statistics or probability theory. The program's strength has been a balanced development of statistical inference based on modern probability while also addressing important problems in applied areas, with the aim of providing solid foundations for basic research, for teaching, and for statistical applications. 

              Ph.D. coursework requires eighteen courses of three credit hours each: six core courses, three of five other basic courses, and six additional courses including at least two from outside the department (to be approved by the curriculum committee). A minimum of 3 dissertation credits is required for graduation. 

                NOTE: Applicants are urged to read the specific Graduate School Requirements for the Ph.D. 

              Basic Courses 

              All Ph.D. students are required to take at least twelve courses in their first two years, including the following three two-semester sequences: 

              Stat 154: Measure and Integration; Stat 155: Probability 
              Stat 164: Statistical Theory I; Stat 165: Statistical Theory II 
              Stat 174: Applied Statistics I; Stat 175: Applied Statistics II 

              Three of the following five other basic courses are required: 

              Stat 184: Stochastic Processes 
              Stat 185: Time Series and Multivariate Analysis 
              Stat 190: Consulting
              Stat 194: Design and Robustness
              Stat 195: Bayesian Statistics and Generlized Linear Models 

              Advanced and Specialized Courses (by area):

              Inference:

              Stat 220. Estimation, Hypothesis Testing,and Statistical Decision
              Stat 221. Sequential Analysis
              Stat 222. Nonparametric Inference: Rank-Based Methods
              Stat 223. Nonparametric Inference: Smoothing Methods
              Stat 224. Statistical Large Sample Theory
              Stat 225. Subsampling Techniques

              Probability and Stochastic Processes:

              Stat 231. Advanced Probability
              Stat 232. Stochastic Processes
              Stat 233. Time Series Analysis
              Stat 234. Extreme Value Theory
              Stat 235. Point Processes
              Stat 236. Stochastic Analysis

              Design of Experiments

              Stat 210. Design and Analysis of Experiments
              Stat 211. Special Topics in the Design of Experiments
              Stat 212. Combinatorial Problems of the Design of Experiments
              Stat 253. Error Correcting Codes 

              Multivariate Analysis

              Stat 260. Multivariate Analysis
              Stat 261. Advanced Parametric Multivariate Analysis
              Stat 262. Nonparametric Multivariate Analysis 

              Communication Theory

              Stat 142. Introduction to Estimation and Detection Theory
              Stat 232. Stochastic Processes
              Stat 252. Information Theory
              Stat 253. Error Correcting Codes

              Applied Statistics Courses

              Stat 302. Seminars in: Data Analysis, Applied Statistics, Statistical Computing. 

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              Examinations 

              The Comprehensive Written Exam (CWE) consists of three papers, one of each of the sequences (154-5, 164-5, 174-5). To pass the CWE a student must pass all three papers, with a high pass on at least two of the papers. [Each student's performance -- high pass, pass, or fail -- on each paper will be determined by the whole faculty in its regular discussion of all CWE results.]

              Normal progress for a Ph.D. student entails the passing of at least two papers of the CWE before the beginning of the student's second year, and the passing of all three papers (with at least two high passes) before the beginning of the third year.

              Each of the three papers will be three hours in duration. The exams will be given on three separate days (for example, on Monday, Wednesday, Friday of a single week).

              A January CWE may be given, in whole or in part, to give certain students an opportunity to retake a failed paper. The faculty will decide, individually for each student, on the appropriateness and desirability of such retake exams.

              Students should aim to take the Preliminary Oral Examination no later than the end of the sixth semester. This is based on an essay including a description of the proposed dissertation topic, a review of the literature, and a bibliography related to the proposed research. At this examination, the student will describe the thesis proposal and answer questions on it, and on the literature reviewed. Students who have passed this oral examination and who wish to obtain an M.S. degree may do so without having to take the final oral examination normally required for the M.S., though they must fulfill the 3 hours of (393) thesis credit requirement to do so. 

              When ready, the candidate will submit the dissertation to the members of his/her committee. At the Final Oral Examination, the candidate presents the dissertation research and conclusions, and answers questions. 

              The number of required sequences taken by a Ph.D. student in the first year will be based on discussions between the student and the student's advisor. Any adjustment of a student's course work made during the first year will be decided by the Committee for Graduate Studies, in consultation with the student and the student's advisor.

              Students who take fewer than three of the required sequences in the first year will be encouraged to supplement their coursework in an appropriate manner, following discussions with the student's advisor. For example, a student may take remedial or background courses in mathematics, or may engage in independent study of background material. Other supplemental courses of action are possible. 

              Recent Ph.D.s, Dissertation Topics and Advisors 

              Anna Admirdjanova (2000), "Topics in stochastic fluid dynamics", Advisor: G. Kallianpur (ABSTRACT)

              Amy Grady (2000), "A higher order expansion for the joint density of the sum and the maximum with applications to the estimation of climatologic al trends", Advisor: R.L. Smith (ABSTRACT)

              Run-ze Li (2000), "High-dimensional modeling via nonconcave penalized liklihood and local likelihood" , Advisors: J. Fan and J.S. Marron (ABSTRACT)

              Greg Spaniolo (2000), "Rice's formula and palm probabilities with applications to structural reliability", Advisor: M.R. Leadbetter (ABSTRACT)

              Georgios Skoulakis (2000), "Superprocesses over a stochastic flow", Advisor: R. Adler (ABSTRACT)

              Chunming Zhang (2000), "Topics in generalized likelihood ratio test", Advisor: J. Fan (ABSTRACT)

              Employment Placement. In the past 6 years, 19 students have received their PhDs. Of these, 7 went into industry or business and 12 took academic positions.