Graduate School Bulletin - Spring 2005

STATISTICS

The Department of Statistics offers programs of study leading to the degrees of Master of Science (Plan A or B available), and Doctor of Philosophy. The M.S. degree is professionally oriented for the student who plans a career in government, business or industry. The Ph.D. program offers a broad training in both statistical theory and methods while affording options to suit the student's interests. The statistics Ph.D. is well-suited for academic, business, government and industrial positions. In addition to formal course work and research training, the advanced student has opportunities to gain valuable practical experience by participating in consulting activities under faculty supervision.

Course work is available in areas associated with statistics such as biological modelling, computer science, control theory, econometrics, mathematics and operations research.

A student intending to pursue a master's degree in statistics should have one course each in advanced calculus (equivalent of MA 432 or 471) and matrix algebra (equivalent of MA 462) for the first year's graduate courses. A graduate level course in real analysis (equivalent of MA 571) is a prerequisite for the Ph.D. core curriculum. If possible, mathematical deficiencies should be corrected during the summer prior to entering the Graduate School.

The University of Kentucky is represented on the Committee on Statistics of the Southern Regional Education Board.

Admission Requirements

Students with an undergraduate major in any of the mathematical, physical, biological, social or applied sciences are encouraged to apply.

The minimum GRE and GPA admissions requirements for the M.S. and Ph.D. programs in Statistics are the same as for the Graduate School, however, the number of admissions is limited and admissions decisions are made on a competitive basis. All M.S. applicants should have at least five semesters of calculus and a course in linear algebra. In addition, all Ph.D. applicants must have an introduction to real analysis course. Students wishing to apply for teaching assistantships and/or fellowships must have three letters of recommendation sent to: Director of Admissions, Department of Statistics, University of Kentucky, 817 Patterson Office Tower, Lexington, KY 40506-0027. Applicants wishing to be admitted directly to the Ph.D. program must have an M.S. in Statistics or the permission of the Director of Admissions.

Master's Program

The Department offers the degree of Master of Science with (Plan A) or without (Plan B) a thesis. The core curriculum expected of all master's degree students consists of the following courses:

STA 503 Introduction to Statistical Methods 4

STA 531 Theory of Probability 3

STA 532 Theory of Statistical Inference I 3

STA 601 Theory of Statistical Inference II 3

STA 603 Introduction to Linear Models and Experimental Design 4

STA 624 Applied Stochastic Processes 3

Programs of study for Plan B require a total of at least 35 semester hours, which should include the equivalent of the six courses in the core curriculum and at least 15 additional credit hours. Of these 15 credit hours, at least 6 should be from the following list of statistics courses:

STA 612 Sequential Analysis 3

STA 616 Design And Analysis of Sample Surveys 3

STA 621 Nonparametric Inference 3

STA 643 Advanced Experimental Design 3

STA 644 Advanced Linear and Nonlinear Models 3

STA 661 Multivariate Analysis I 3

STA 665 Analysis of Categorical Data 3

Programs of study for Plan A (with thesis) require a total of at least 29 semester hours, which should include the core curriculum and at least two courses from the previous list. Candidates should also satisfy the requirements that at least 18 hours for Plan B and 15 hours of non-thesis courses for Plan A must be at the 600 level or higher. The free electives courses can be selected from a variety of courses both within and outside the Department of Statistics. Before the end of the second semester, the M.S. candidate must present a proposed plan of study for approval by the Director of Graduate Studies. There are no formal minor requirements.

All master's candidates are required to take a departmental written examination on the core curriculum. These exams are normally administered in August.

Doctoral Program

The doctorate is a research degree that demonstrates independent and comprehensive scholarship and is granted on the basis of broad statistical competence and the exhibition of creative ability. There are thus two components to the doctoral program: 1) a comprehensive program of probability, statistics and related courses, and 2) in-depth research in a particular area and the preparation, under faculty supervision, of a dissertation.

Students in the doctoral program in Statistics will choose one of two possible tracts:

Mathematical Statistics/Probability Biostatistics
STA 701 – Advanced Statistical Inference I STA 701 – Advanced Statistical Inference I
STA 703 – Advanced Probability STA 703 – Advanced Probability
STA 705 – Advanced Computational Inference STA 705 – Advanced Computational Inference
STA 707 – Advanced Data Analysis STA 707 – Advanced Data Analysis
STA 702 – Advanced Statistical Inference II STA 709 – Advanced Survival Analysis

All students must take an additional six courses chosen by the student and approved by the DGS. Three of these will complement and supplement the student’s specialization area and research interests. STA 715 (Reading courses) may not be used to satisfy this requirement.

The new course schedule can be summarized as follows:

Fall, Year One STA 503 STA 531 STA 532
Spring, Year One STA 601 STA 603 STA 624
Fall, Year Two STA 643 STA 700 Elective
Spring, Year Two STA 701 STA 703 Elective
Fall, Year Three STA 707 STA 705 Elective
Spring, Year Three STA 702/709 Elective Elective
Fall, Year Four Elective Residency Residency
Spring, Year Four Elective Residency Residency

Students must successfully complete a common written exam over STA 701 and STA 703 plus respective prerequisites. This exam will normally be offered in June and students will usually sit for the written examination at the end of the second year of the program.

After completion of course requirements and successful completion of the written exam, Students must also successfully complete an oral qualifying exam administered by their committee. A significant part of this exam is to be a dissertation proposal.

Areas of current research interest are:

a) mathematical statistics including statistical inference, categorical data analysis, nonparametric models, asymptotic theory, sequential analysis, decision theory;

b) statistical analysis and design including the design of experiments, variance components models, linear and non-linear models;

c) stochastic processes including applications of probability in biology, queueing and storage systems, reliability.

All students, master's and doctoral, will be required to take part in an internship program. This will usually consist of teaching (three or six semester hours) or an equivalent amount of work in the Statistics Consulting Laboratory or the Biostatistics Consulting Unit.

GRADUATE COURSES

STA 417G PRINCIPLES OF OPERATIONS RESEARCH II (SAME AS MA 417G) (3)

STA 422G BASIC STATISTICAL THEORY II (4)

STA 503 INTRODUCTION TO STATISTICAL METHODS (4)

STA 515 MATHEMATICAL PROGRAMMING AND EXTENSIONS (SAME AS MA 515) (3)

STA 524 PROBABILITY (SAME AS OR 524) (3)

STA 525 INTRODUCTORY STATISTICAL INFERENCE (SAME AS OR 525) (3)

STA 531 THEORY OF PROBABILITY (3)

STA 532 THEORY OF STATISTICAL INFERENCE I (3)

STA 570 BASIC STATISTICAL ANALYSIS (4)

STA 580 BIOSTATISTICS I (3)

STA 600 COMMUNICATING IN STATISTICS (0)

STA 601 THEORY OF STATISTICAL INFERENCE II (3)

STA 603 INTRODUCTION TO LINEAR MODELS AND EXPERIMENTAL DESIGN (4)

STA 612 SEQUENTIAL ANALYSIS (3)

STA 616 DESIGN AND ANALYSIS OF SAMPLE SURVEYS (3)

STA 619 PROBLEMS SEMINAR IN OPERATIONS RESEARCH (SAME AS EE 619/MA 613) (3)

STA 621 NONPARAMETRIC INFERENCE (3)

STA 624 APPLIED STOCHASTIC PROCESSES (SAME AS OR 624) (3)

STA 626 TIME SERIES ANALYSIS (SAME AS ECO 790) (3)

STA 630 BAYESIAN INFERENCE (3)

STA 635 SURVIVABILITY AND LIFE TESTING (3)

STA 643 ADVANCED EXPERIMENTAL DESIGN (3)

STA 644 ADVANCED LINEAR AND NONLINEAR MODELS (3)

STA 653 CLINICAL TRIALS (3)

STA 661 MULTIVARIATE ANALYSIS I (3)

STA 662 RESAMPLING AND RELATED METHODS (3)

STA 665 ANALYSIS OF CATEGORICAL DATA (3)

STA 671 REGRESSION AND CORRELATION (2)

STA 672 DESIGN AND ANALYSIS OF EXPERIMENTS (2)

STA 673 DISTRIBUTION-FREE STATISTICAL INFERENCE AND ANALYSIS OF CATEGORICAL DATA (2)

STA 675 SURVEY SAMPLING (2)

STA 676 QUANTITATIVE INHERITANCE IN PLANT POPULATIONS (SAME AS PLS 676) (3)

STA 677 APPLIED MULTIVARIATE METHODS (3)

STA 679 DESIGN AND ANALYSIS OF EXPERIMENTS II (3)

STA 690 SEMINAR IN STATISTICS (1)

STA 691 SPECIAL TOPICS IN THE PLANNING AND ANALYSIS OF EXPERIMENTS (SUBTITLE REQUIRED) (1-3)

STA 692 STATISTICAL CONSULTING (3)

STA 695 SPECIAL TOPICS IN STATISTICAL THEORY (SUBTITLE REQUIRED) (1-3)

STA 700 FOUNDATIONS OF PROBABILITY AND INFERENCE (3)

STA 701 ADVANCED STATISTICAL INFERENCE I (3)

STA 702 ADVANCED STATISTICAL INFERENCE II (3)

STA 703 ADVANCED PROBABILITY (3)

STA 704 ADVANCED PROBABILITY - STOCHASTIC PROCESSES (3)

STA 705 ADVANCED COMPUTATIONAL INFERENCE (3)

STA 707 ADVANCED DATA ANALYSIS (3)

STA 709 ADVANCED SURVIVAL ANALYSIS (3)

STA 715 READINGS IN STATISTICS AND PROBABILITY (SUBTITLE REQUIRED) (1-6)

STA 748 MASTER'S THESIS RESEARCH (0)

STA 749 DISSERTATION RESEARCH (0)

STA 768 RESIDENCE CREDIT FOR MASTER'S DEGREE (1-6)

STA 769 RESIDENCE CREDIT FOR THE DOCTOR'S DEGREE (0-12)

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