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.

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.

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. Students in this program should also have prior exposure to computing using business software, statistical software such as SAS or SPSS, and an interactive programming environment such as C,  R or Matlab.

The concentration requires completing 10 courses, organized around five broad areas of expertise. The first course in probability and statistics, STAT 410, may be waived for students entering with credit for the same or an equivalent course. The 10 required courses by area are described below, and a flat list of courses can be found in the Academic Catalog.

For course descriptions and availability per semester, please see the Academic Catalog.

Mathematical Statistics

• STAT 410 - Statistics and Probability II - (4 hours)
• STAT 510 - Mathematical Statistics (4 hours)

STAT 410 is a course in probability and mathematical statistics and prepares students for STAT 510, a practical advanced graduate level course mathematical statistics course. These courses form the foundation for statistical inference that is encountered throughout the remainder of the curriculum. STAT 410 may be waived for students entering with credit for the same or an equivalent course.

Foundational Applied Statistics

• STAT 425 - Statistical Modeling I (4 hours) or
• STAT 527 - Advanced Regression Analysis (4 hours)

Select 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.}}

The choice of STAT 425 or STAT 527 provides thorough coverage of linear regression and data analysis that is fundamental for further study in analytics. STAT 527 is the more advanced course required for PhD students. The second course is a selection of one of several traditional courses in foundational areas of statistics.

Statistical Computing

• STAT 440 - Statistical Data Management (4 hours)
• STAT 448 - Advanced Data Analysis (4 hours)

Select one of the following - 4 hours:

• STAT 428 - Statistical Computing (4 hours)
• STAT 432 - Basics of Statistical Learning (4 hours)
• STAT 437 - Unsupervised Learning (4 hours)
• STAT 447 - Data Science Programming Methods (4 hours)
• STAT 480 - Big Data Analytics (4 hours)
• CS 412 - Introduction to Data Mining (4 hours)*
  ^{*This course is not controlled by the Statistics Department, please see CS on how to register for this course.} 

STAT 440 focuses on data management and sampling skills vital for success in information intensive careers. STAT 448 is a survey of common advanced statistical methods with an emphasis on application in a computational setting. The third course is a choice of computational courses focused on foundations of statistical computation, data science, or data mining.

Advanced Analytics

• STAT 542 - Statistical Learning (4 hours)

Select one of the following - 4 hours: 

• STAT 525 - Computational Statistics (4 hours)
• STAT 546 - Machine Learning in Data Science (4 hours)
• STAT 571 - Multivariate Analysis (4 hours)
• CS 512 - Data Mining Principles (4 hours)*
  ^{*This course is not controlled by the Statistics Department, please see CS on how to register for this course}

STAT 542 is an advanced course in statistical learning that covers stat-of-the-art and proven methods for classification, clustering, model selection, and predictive modeling in the context of large data sets. The second advanced analytics course is a choice of advanced statistical computing theory, multivariate analysis, data mining, and machine learning courses.

Experiential Learning

Select one of the following - 4 hours: 

• STAT 427 – Statistical Consulting (4 hours)
• STAT 443 – Professional Statistics (4 hours)
• STAT 593 – STAT Internship (0 or 4 hours)

Team problem solving and communication of statistical results is critical for career success. The experiential learning requirement focuses on these skills and is a choice of consulting, professional preparation or approved internship.

The University of Illinois uses the "Slate" online application system. To use this system, follow the directions at https://grad.illinois.edu/admissions/apply

There is a nonrefundable application fee. Please see the Graduate Application Instructions for current application fees for domestic and international applicants.

Applicants should be prepared to provide all current and previous unofficial transcripts through the application system for consideration. For review purposes, the Department will only need the unofficial reports attached to your application. Though the Department prefers new letters of recommendations, up to two letters previously submitted to your current degree program can be re-used, however they must still be submitted by the recommender through the application system or provided directly from your current program's administrative office. Applicant's should have at least one new letter submitted on their behalf. 

If admitted to the program you will be contacted by the Graduate Program Coordinator with detailed instructions on the petition process and what needs to be included with the petition to the Graduate College. 

The prerequisites for the program include calculus through multivariable calculus, linear algebra equivalent to MATH 257 or MATH 415, and an introduction to mathematical statistics and probability equivalent to STAT 400.

Curriculum Requirements in Statistics

4 courses / 16 credit hours

• STAT 410* (Statistics & Probability II) ^{_{*This requirement can be waived if the student has already taken the course, or a course equivalent to it at another institution.}}
• STAT 425 (Statistical Modeling I)
• Simultaneous enrollment in a PhD program that uses statistics.
• Two additional Statistics courses not already used to fulfill a requirement:
  Eligible courses include STAT 424, 426, 427, 428, 429, 430, 431, 432, 433, 434, 437, 440, 443, 447, 448, 458, 466, 480, 510, 511, 525, 527, 528, 530, 533, 534, 542, 545, 546, 551, 552, 553, 554, 555, 556, 558, 571, 575, 576, 578, 587, and 588.

Course Requirements in Primary Field of Study

5 courses / 20 credit hours

In addition to the core Statistics courses selected above, 5 additional graduate courses (equaling 20 credit hours) relevant to your primary field and the field of Statistics must be completed. These 5 courses can be courses from the following list or courses from the "Two additional Statistics courses" list above which are not used toward any degree requirement.

The approved primary field of study courses outside the Statistics Department are as follows: