Coursework

Course Requirements

Prerequisite

  • MATH 447 Real Variables (*Waived if a course at an equivalent level has been taken at another institution and a grade of B or above is achieved)

MS Equivalent Core (16 credits)

  • STAT 424 Analysis of Variance
  • STAT 426 Sampling and Categorical Data
  • STAT 510 Mathematical Statistics I
  • STAT 527 Advanced Regression Analysis (effective FA19, replaces STAT 425 as a MS Equivalent Core)

Theory Core Courses (12 credits)

  • STAT 511 Mathematical Statistics II
  • STAT 553 Probability and Measure I
  • STAT 575 Large Sample Theory

Select one Practicum Course: (4 credits)

  • STAT 427 Statistical Consulting
  • STAT 593 STAT Internship
  • STAT 595 Preparing Future Faculty

Select one Computational Theory and Methods Course: (4 credits)

  • STAT 428 Statistical Computing
  • STAT 525 Computational Statistics
  • STAT 530 Bioinformatics
  • STAT 542 Statistical Learning

Select one of the Stochastic Processes and Time Series Courses: (4 credits)

  • STAT 429 Time Series Analysis
  • STAT 433 Stochastic Processes
  • STAT 554 Probability and Measure II
  • STAT 555 Applied Stochastic Processes

Select at least 3 elective courses not used above, from the list of electives below. At least two courses must be at the 500-level. (12 credits)

Statistics Courses:

  • STAT 427 - Statistical Consulting
  • STAT 428 - Statistical Computing
  • STAT 429 - Time Series Analysis
  • STAT 430 - Topics in Applied Statistics
  • STAT 431 - Applied Bayesian Analysis
  • STAT 432 - Basics of Statistical Learning
  • STAT 433 - Stochastic processes (pending approval)
  • STAT 434 - Survival Analysis 1
  • STAT 440 - Data Management
  • STAT 448 - Advanced Data Analysis
  • STAT 458 - Math Modeling in Life Sciences
  • STAT 466 - Image and Neuroimage Analysis
  • STAT 525 - Computational Statistics
  • STAT 530 - Bioinformatics
  • STAT 534 - Advanced Survival Analysis
  • STAT 538 - Clinical Trials Methodology
  • STAT 542 - Statistical Learning
  • STAT 545 - Spatial Statistics
  • STAT 551/Math561 - Theory of Probability I
  • STAT 552/Math562 - Theory of Probability II
  • STAT 554 - Probability and Measure II
  • STAT 555 - Applied Stochastic Processes
  • STAT 571 - Multivariate Analysis
  • STAT 578 - Topics in Statistics (if the topic is different, it can be taken multiple times and counted as a different course)
  • STAT 587 - Hierarchical Linear Models
  • STAT 588 - Covariance Structures and Factor Models
  • STAT 593 - Internship
  • STAT 595 - Preparing Future Faculty

Approved elective courses offered by other departments (other courses subject to approval by the PhD committee)

  • CS 512 - Data Mining Principles
  • CS 543 - Computer Vision
  • CS 546 - Machine Learning in NLP
  • CS 573 - Algorithms
  • CS 583 - Approximation Algorithms
  • ECE 547 - Topics in Image Processing
  • ECE 561 - Detection and Estimation Theory
  • ECE 563 - Information Theory
  • ECE 580 - Optimization by Vector Space Methods
  • ECON 536 - Applied Econometrics
  • ECON 574 - Econometrics I
  • ECON 575 - Econometrics II
  • ECON 576 - Time Series
  • ECON 590 - Applied Macroeconometrics
  • ECON 590 - Applied Financial Econometrics
  • IE 510 - Applied Nonlinear Programming
  • IE 521 - Convex Optimization
  • IE 528 - Computing for Data Analytics
  • IE 529 - Stats of Big Data & Clustering
  • MATH 540 - Real Analysis
  • MATH 580 - Combinatorial Mathematics
  • MATH 585 - Probabilistic Combinatorics
  • MATH 588 - Optimization in Networks
  • MATH 589 - Conjugate Duality and Optimization

Thesis and Individual Study Courses (0-32 credits)

  • STAT 590 Individual Study and Research (0 to 8 credits)
  • STAT 599 Thesis Research (0 min applied toward degree)

Total Hours 64

Other Requirements

Other requirements may overlap

Masters Degree Required for Admission to PhD? No, but Masters level requirements must be met (32 additional hours min)

Qualifying Exam Required? Yes

Preliminary Exam Required? Yes

Final Exam/Dissertation Defense Required? Yes

Dissertation Deposit Required? Yes

Minimum GPA: 2.75

Course Sequences

Students admitted without deficiencies (i.e., who are not on "Limited Status") take Statistics 425 and Statistics 510 in their first semester of study, and Statistics 424, Statistics 426, and Statistics 511 in the second semester. The student will be ready to take the PhD qualifying exam after the first two semesters. The typical PhD course sequence is as follows: 

Course Sequence

Students who have taken real analysis previously may waive Mathematics 447 with approval from the PhD program director.

International students are expected to meet certain English Proficiency requirements if they will have classroom duties as part of their assistantship (see ENGLISH PROFICIENCY INTERVIEW FOR INTERNATIONAL TEACHING ASSISTANTS). If TOEFL/IELTS speaking scores were not high enough to meet this teaching requirement at admission, the student is expected to complete an oral English Proficiency Interview (EPI) on campus during their first year as PhD students . Because teaching is fundamental to both financial support and career development, international students who do not complete these requirements by January of the second year are subject to a reduction in financial aid.