Master of Science in Statistics

The Master of Science (MS) degree in Statistics provides advanced training in mathematical and applied statistics, exposure to statistics in a consulting or collaborative research environment and specialized coursework in a number of areas of emphasis. The program is intended to prepare students for careers as practicing statisticians, to provide enhanced research expertise for students pursuing advanced degrees in other fields, and to strengthen the mathematical and statistical training of students preparing for PhD studies in statistics or a related field. The MS degree requires 32-36 hours (8 or 9 courses) beyond the prerequisites. There is no thesis requirement for this degree. The entire program must be approved by the Graduate Advisor before a degree can be awarded.

Prerequisites

The prerequisites for the program include calculus through multivariable calculus, linear algebra equivalent to MATH 257, and an introduction to mathematical statistics and probability equivalent to STAT 400.

Course Requirements

A. Four required courses (12 or 16 hours)
(For course descriptions, visit the Academic Catalog.)

1. STAT 410 - Statistics and Probability II (4 hours)*

*This requirement can be waived if the student has already taken the course, or a course equivalent to it at another institution. (4 hours)

2. One of the following (4 hours)

  • STAT 425 - Statistical Modeling I
  • STAT 527 - Advanced Regression Analysis I

3. One of the following (4 hours)

  • STAT 424 - Design of Experiments
  • STAT 426 - Statistical Modeling II
  • STAT 429 - Time Series Analysis
  • STAT 431 - Applied Bayesian Analysis
  • STAT 433 - Stochastic Processes
  • STAT 528 - Advanced Regression Analysis II
  • STAT 533 - Advanced Stochastic Processes
  • STAT 556 - Advanced Time Series Analysis
    Note: For students who entered the program prior to Fall 2021, the listed options for this item are STAT 424, STAT 426, STAT 429, STAT 430, and 578.

4. STAT 510 - Mathematical Statistics (4 hours)

B. Five elective courses (20 hours)
(For course descriptions, visit the Academic Catalog.)

At least 12 hours must be from the following list, and any course used to satisfy A2 or A3 may not also be used to satisfy B. Up to 8 hours may be from other units on campus, subject to the approval of the Graduate Advisor. All courses below are four hours except STAT 590 and STAT 593, which have a variable number of hours.

  • STAT 424 - Design of Experiments
  • STAT 426 - Statistical Modeling II
  • 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
  • STAT 434 - Survival Analysis
  • STAT 437 - Unsupervised Learning
  • STAT 440 - Data Management
  • STAT 443 - Professional Statistics
  • STAT 447 - Data Science Programming Methods
  • STAT 448 - Advanced Data Analysis
  • STAT 458 - Math Modeling in Life Sciences
  • STAT 466 - Image Analysis
  • STAT 480 - Big Data Analytics
  • STAT 511 - Mathematical Statistics II
  • STAT 525 - Computational Statistics
  • STAT 527 - Advanced Regression Analysis I
  • STAT 528 - Advanced Regression Analysis II
  • STAT 530 - Bioinformatics
  • STAT 533 - Advanced Stochastic Processes
  • STAT 534 - Advanced Survival Analysis
  • STAT 542 - Statistical Learning
  • STAT 545 - Spatial Statistics
  • STAT 546 - Machine Learning in Data Science
  • STAT 551 - Theory of Probability I
  • STAT 552 - Theory of Probability II
  • STAT 553 - Probability and Measure I
  • STAT 554 - Probability and Measure II
  • STAT 555 - Applied Stochastic Processes
  • STAT 556 - Advanced Time Series Analysis
  • STAT 558 - Risk Modeling and Analysis
  • STAT 571 - Multivariate Analysis
  • STAT 575 - Large Sample Theory
  • STAT 576 - Empirical Process Theory and Weak Convergence
  • STAT 578 - Topics in Statistics
  • STAT 587 - Hierarchical Linear Models
  • STAT 588 - Covariance Structures and Factor Models
  • STAT 590 - Reading Course (at most four hours total for this course)
  • STAT 593 - Internship (at most four hours total for this course)

C. Experience with statistical practice in an interdisciplinary environment
(For course descriptions, visit the Academic Catalog.)

This requirement is satisfied by any one of the following:

  1. STAT 427 - Statistical Consulting; or
  2. STAT 443 - Professional Statistics; or
  3. STAT 593 - Internship; or
  4. For students previously or concurrently admitted to another graduate program at the University of Illinois that uses statistics, completing at least 12 graduate hours (3 courses) in that program. The 12 hours would not count toward the MS degree in Statistics.

If STAT 427, STAT 443, or STAT 593 is taken to meet this requirement, those hours can count toward the 20 described in B.

D. Graduate level course requirement

At least 12 hours (3 courses) must be taken at the 500 level and at least 2 of the 500 level courses must be STAT courses.

Other Requirements: 

2.75 Minimum GPA