College of Arts & Sciences

Statistics - Graduate

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The Department of Statistics offers programs of study leading to the degrees of Master of Science (Plan A or B available), Doctor of Philosophy, and Master of Applied Statistics (Online).  Both, the M.S. and the Ph.D. program offer a Mathematical Statistics track, as well as a Biostatistics track. The latter tracks are designed for students who envision a future at the interface of Statistics and the Life Sciences.

Application Requirements

Admissions Information

This page contains links to a variety of information concerning the admissions process to the Department of Statistics at the University of Kentucky, including how to apply and a frequently asked questions (FAQ) section. More information on the graduate program itself and requirements for admission may be found in our program descriptions. If you have any questions not addressed by those sources, send email to stat-admit@ms.uky.edu

Applying to the Graduate Program in Statistics

Applications are submitted and processed electronically through the Graduate School Apply Yourself portal Applicants to the M.S. program must choose Admissions Category - Masters Degree and in application choose Program - Statistics - MS. Make sure to choose the M.S. program in Statistics even if you plan on pursuing a Ph.D. later or if you already have a Master of Science in Statistics. Although the department has rolling admissions, applicants are urged to have all materials in by February 1 to maximize the chances for assistantships and fellowships.

How to Apply for Admission

All applications for graduate study at the University of Kentucky Graduate School must be submitted on-line. DO NOT SEND MATERIALS TO THE DEPARTMENT or to stat-admit@uky.edu unless specifically requested by the Director of Graduate Studies.  See the Graduate School website for further details. We are now part of the Hobsons ApplyYourself Application Network, a system used by over 700 colleges and universities that provides an opportunity to submit all Graduate School and program requirements in one application, including letters of recommendation. Each application requires completion of a separate application form and submission of a separate application fee. Currently the fee for domestic applicants is $65.00 per application and for international applicants the fee is $75.00. Please note that the application cannot be submitted without payment of this fee.

Step one in the process is to set up a new account and establish a user name and password. Do not lose this information; you will need it if you wish to return to continue an unfinished application or review a completed application.

In order to complete the application you will need to gather several pieces of information including the following:

Transcripts

You will be asked to upload copies of transcripts from all higher education institutions attended and, in the case of domestic students, to self-report cumulative GPA’s for each institution. For degree-seeking students, the Graduate School requires an overall undergraduate grade point average of 2.75 and 3.00 on all graduate work. If you are offered admission and decide to enroll you will then be required to submit official transcripts to the Graduate School.

Test Scores

For formal admission to the graduate program in Statistics, an official GRE test score is required. You will be asked to self-report these scores on the application (you can also supply a future date for taking the test). Your application, with self-reported scores, will be processed by the admissions committee.  However, we also require official scores from the reporting agency before your matriculation.

  • If you are admitted to the graduate program in Statistics, GRE scores should be sent directly to us from Educational Testing Service (ETS); the Institution Code for the GRE for UK Graduate School is R1837.
  • GRE Quantitative Score Percentiles for recently admitted students: Lower Quartile=89%; Median=94%; and Upper Quartile=97%.

These scores will be incorporated into your application and compared against self-reported scores to ensure consistency. The Graduate School sets no minimum score for the GRE; admission to the Statistics program is competitive and the quantitative GRE is heavily weighted. See the above bullet for information on GRE quantitative scores for recently admitted students.

TOEFL or IELTS Scores

All applicants whose native language is not English will be asked to self-report one of these scores on the application. As for GRE scores, we also require official language scores to be sent to us directly from the reporting agency if you are admitted to the graduate program in Statistics.

  • If you are admitted to the graduate program in Statistics, TOEFL scores should be sent directly to us from Educational Testing Service (ETS); the Institution Code for the TOEFL for UK Graduate School is R1837.
  • If you are admitted to the graduate program in Statistics, IELTS scores should be sent directly to us from the International English Language Testing Service specifying the University of Kentucky Graduate School, Lexington, Kentucky as the recipient institution.
  • TOEFL IBT Scores for recently admitted MS students: Lower Quartile=89; Median=96; and Upper Quartile=102%.

For the Graduate School, the minimum acceptable TOEFL score is 550 (paper-based) 213 (computer-based), or 79 (internet-based). The minimum IELTS score is 6.5; the graduate program in Statistics has a higher requirement.  See the above bullet for information on recently admitted students.  Official submitted scores must be no more than two years old.  All international applicants must provide TOEFLscores for financial support.  

Letters of Recommendation

The graduate program in Statistics also requires letters of recommendation. As part of the application you will be asked to supply contact information for three recommenders.  Once your application has been submitted, the system will contact each person identified and their recommendations will be submitted directly to us. You can check back into your application at any time to see who has submitted a recommendation. You can also review recommender requirements via the following link: http://www.gradschool.uky.edu/prospectivestudents/program_reqs.html

Application Deadlines

For domestic applicants and applicants to the Master of Applied Statistics, the Graduate School requires applications to be submitted no later than one month prior to the start of the term for which the applicant intends to begin graduate work. Please refer to the Academic Calendar for typical semester starting dates. For international applicants to the M.S. and PhD programs, the following Graduate School deadline applies: Fall Semester Admission - March 15th

New students are admitted to the graduate program in Statistics only for the Fall Semester.  Conditional admission to complete pre-requisites is available in all semesters.

Doctoral Program

Doctoral Program in Statistics
Mathematical Statistics or Biostatistics Track

The Statistics Department offers a Doctoral Program with two different tracks that students can choose from: A Mathematical Statistics track and a Biostatistics track. Both tracks are designed to provide doctoral candidates with a firm foundation on probability theory, inference, and classical methodology. In addition, the theory and application of statistical computing, and graphical as well as computer based inference are integral parts of the core curricula. The Biostatistics track provides students the opportunity to focus on one important area of statistical research, namely on the methodology and application of statistics in the life sciences. There is no direct link between the Mathematical Statistics and Biostatistics tracks in the MSc and the Doctoral programs, respectively. That is, a student can pursue a MSc in the Mathematical Statistics track, and then a PhD in the Biostatistics track.

The requirements for the two tracks are:

Mathematical Statistics/Probability

  • STA 701 – Advanced Statistical Inference I
  • STA 702 – Advanced Statistical Inference II
  • STA 703 – Advanced Probability
  • STA 705 – Advanced Computational Inference
  • STA 707 – Advanced Data Analysis

Biostatistics

  • STA 701 - Advanced Statistical Inference I
  • STA 703 - Advanced Probability
  • STA 705 - Advanced Computational Inference
  • STA 707 - Advanced Data Analysis
  • 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 six electives must be chosen from among STA 612, STA 616, STA 621, STA 624, STA 626, STA 630, STA 635, STA 643, STA 644, STA 653*, STA 661, STA 662, STA 665, CPH 631, CPH 636, and CPH 664*. STA 695 will also be considered on a case by case basis. A course that is required for the selected track may not be used as an elective.

* A student who takes both STA 653 and CPH 664, may only receive credit towards the degree for one of these two courses.

In the following, typical course schedules for both tracks are summarized. Several alternative paths are possible. It is clear from the above track requirements that the only difference in required courses is between STA 702 and STA 709. However, in practice, students often choose to take both of those classes, one for the track, and the other as an elective.

 

Mathematical Statistics Track: Typical Course Schedule

Fall, Year One STA 602 Introduction to Statistical Methods STA 605 Computational Inference STA 623 Theory of Probability
Spring, Year One STA 603 Introduction to Linear Models and Experimental Design STA 606 Theory of Statistical Inference I STA 624 Applied Stochastic Processes
Fall, Year Two STA 607 Theory of Statistical Inference II STA 643 Advanced Experimental Design MA 471G or Elective
Spring, Year Two STA 632 Longitudinal Data Analysis STA 700 Foundations of Probability and Inference Elective
Fall, Year Three STA 701 Advanced Statistical Inference I STA 703 Advanced Probability Elective
Spring, Year Three STA 702 Advanced Statistical Inference II STA 705 Advanced Computational Inference STA 707 Advanced Data Analysis
Fall, Year Four Elective Residency Residency
Spring, Year Four Elective Residency Residency

 

Biostatistics Track: Typical Course Schedule

Fall, Year One STA 602 Introduction to Statistical Methods STA 605 Computational Inference STA 623 Theory of Probability
Spring, Year One STA 603 Introduction to Linear Models and Experimental Design STA 606 Theory of Statistical Inference I STA 653 Clinical Trials
Fall, Year Two STA 607 Theory of Statistical Inference II STA 635 Survivability and Life Testing STA 643 Advanced Experimental Design
Spring, Year Two STA 632 Longitudinal Data Analysis STA 665 Analysis of Categorical Data STA 700 Foundations of Probability and Inference
Fall, Year Three STA 701 Advanced Statistical Inference I STA 703 Advanced Probability Elective
Spring, Year Three STA 705 Advanced Computational Inference STA 707 Advanced Data Analysis STA 709 Advanced Survival Analysis
Fall, Year Four Elective Residency Residency
Spring, Year Four Elective Residency Residency

Master's Program in Statistics

Mathematical Statistics or Biostatistics Track

 

The Statistics Department offers the degree of Master of Science with (Plan A) or without (Plan B) a thesis, and in two different tracks: A Mathematical Statistics track and a Biostatistics track.

Shared Core

 

  • STA 602 (4) Introduction to Statistical Methods
  • STA 603 (4) Introduction to Linear Models and Experimental Design
  • STA 605 (3) Computational Inference
  • STA 606 (3) Theory of Statistical Inference I
  • STA 623 (3) Theory of Probability
  • STA 632 (3) Longitudinal Data Analysis

Mathematical Statistics Track

Curriculum requirements for the Mathematical Statistics track are the shared core courses above, plus the following courses:

  • STA 607 (3) Theory of Statistical Inference II
  • STA 624 (3) Applied Stochastic Processes
  • STA 643 (3) Advanced Experimental Design

Biostatistics Track

Curriculum requirements in the Biostatistics track are the shared core courses above, plus:

  • STA 635 (3) Survivability and Life Testing
  • STA 653 (3) Clinical Trials
  • STA 665 (3) Analysis of Categorical Data
  • STA 693 (2) Biostatistical Practicum, 1 unit course in each of the two semesters in the second year

Programs of study for Plan B require a total of at least 35 semester hours. Students will typically fulfill this requirement by taking electives (additional courses besides the shared core and track requirements) in Fall and Spring of their second year. Programs of study for Plan A (with thesis) require a total of at least 29 semester hours which are satisfied by either of the two course lists above.

The electives can be selected from the menu of courses listed below.

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.

Comprehensive Examination

All master's candidates are required to pass a comprehensive departmental written examination on the content of the courses STA 602, STA 603, STA 605, STA 606, and STA 623. This examination is normally administered in late May/early June. It is truly comprehensive also in the sense that all parts must be taken together: If a student decides not to take a part of the examination, that part is automatically counted as failed. Students taking the comprehensive exam will receive either a pass at the doctoral level, a pass at the master's level, or a failure. The examination may be repeated only once.

Successful completion of the comprehensive examination at the doctoral level is required for admission into the PhD program.

Electives

The electives may be chosen from any course in the following menu that is NOT a track requirement.

  • MA 471G (3) Advanced Calculus I
  • STA 607 (3) Theory of Statistical Inference II
  • STA 612 (3) Sequential Analysis
  • STA 616 (3) Design and Analysis of Sample Surveys
  • STA 621 (3) Nonparametric Inference
  • STA 624 (3) Applied Stochastic Processes
  • STA 626 (3) Time Series Analysis
  • STA 630 (3) Bayesian Inference
  • CPH 631 (3) Design and Analysis of Health Surveys
  • STA 635 (3) Survivability and Life Testing
  • CPH 636 (3) Data Mining in Public Health
  • STA 643 (3) Advanced Experimental Design
  • STA 644 (3) Advanced Linear and Nonlinear Models
  • STA 653 (3)* Clinical Trials
  • STA 661 (3) Multivariate Analysis I
  • STA 662 (3) Resampling and Related Methods
  • CPH 664 (3)* Design and Analysis of Clinical Trials
  • STA 665 (3) Analysis of Categorical Data

Any course on this list NOT required for the chosen track may be used as an elective. Thus, for example, STA 665 would count as an elective for the Mathematical Statistics track, but it is a track requirement for the Biostatistics track. Similarly, STA 624 would be an elective for the Biostatistics track but is a track requirement for the Mathematical Statistics track.

* A student who takes both STA 653 and CPH 664, may only receive credit towards the degree for one of these two courses.

Recommended Schedule

In the following schedule, whenever two courses are listed (e.g. STA624/STA653), the first is taken in the Mathematical Statistics track, and the second in the Biostatistics track.
The electives ("elec") can be anything from the elective list, including courses required for the respective other track.
Fall year 1 - STA602, STA605, STA623
Spring year 1 - STA603, STA606, STA624/STA653
Fall year 2 - STA607/elec, elec/STA635, STA643/elec, nothing/STA693
Spring year 2 - STA632, elec/STA665, elec, nothing/STA693

If you are planning on continuing for a PhD:
(1) Take STA607 and STA643 in Fall year 2, either as track requirements or electives.
(2) If you haven’t yet taken MA471G before, it should be taken in Fall year 2.
(3) Take STA700 in Spring year 2.

Master of Applied Statistics (Online)

The Master of Applied Statistics curriculum consists of 11 online courses that focus on the discovery of statistical techniques and approaches through data visualization and computing. They will provide students with a firm understanding of linear and nonlinear models, and will prepare graduates to function in a variety of roles such as data analyst, data management technician and statistical programmer.

The selection of 11 online courses includes five required courses (17 hours) and 13 hours of guided electives selected from six courses.

Course Course Title Prerequisites Hours
STA 645* (Intro Video) Computational Theory and Data Visualization   3
STA 646* (Intro Video) Foundations of Probability and Inference STA 645 4
STA 647* (Intro Video) Statistical Computing with SAS   2
STA 648* (Intro Video) Regression Modeling STA 645 4
STA 649* (Intro Video) Design of Experiments STA 648 4
STA 650 Applied Multivariate Statistics STA 646 3
STA 651 (Intro Video) Advanced Programming with R   1
STA 652 Advanced Statistical Modeling STA 648 3
STA 654 Applied Bayesian Analysis STA 646 3
STA 656 Statistical Quality Control STA 645 3
STA 659 Advanced Statistical Methods   3 (Repeatable up to 6 hours)

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