This is a named option in the Statistics M.S.

Please consult the table below for key information about this degree program’s admissions requirements. The program may have more detailed admissions requirements, which can be found below the table or on the program’s website.

Graduate admissions is a two-step process between academic programs and the Graduate School. Applicants must meet the minimum requirements of the Graduate School as well as the program(s). Once you have researched the graduate program(s) you are interested in, apply online.

Fall Deadline January 2
Spring Deadline The program does not admit in the spring.
Summer Deadline The program does not admit in the summer.
GRE (Graduate Record Examinations) Required. *
English Proficiency Test Every applicant whose native language is not English or whose undergraduate instruction was not in English must provide an English proficiency test score and meet the Graduate School minimum requirements (https://grad.wisc.edu/apply/requirements/#english-proficiency).
Other Test(s) (e.g., GMAT, MCAT) n/a
Letters of Recommendation Required 3
*

Due to COVID-19, there have been challenges for students attempting to take the GRE. Currently, the GRE requirement is waived. Regardless of whether GRE scores are submitted, all applications will be held in equal regard.

Students holding a bachelor's degree with a natural science, social science, or engineering major and strong mathematical background are encouraged to apply for admission to the graduate program in statistics. Students are advised to undertake graduate work in statistics only if their undergraduate grades in mathematics were uniformly high. 

Graduate School Resources

Resources to help you afford graduate study might include assistantships, fellowships, traineeships, and financial aid. Further funding information is available from the Graduate School. Be sure to check with your program for individual policies and restrictions related to funding.

PROGRAM RESOURCES

Each option within Statistics has different funding policies and opportunities for students. Please see each option for details.

Minimum Graduate School Requirements

Review the Graduate School minimum academic progress and degree requirements, in addition to the program requirements listed below.

Named Option Requirements

MODE OF INSTRUCTION

Face to Face Evening/Weekend Online Hybrid Accelerated
Yes No No No No

Mode of Instruction Definitions

Accelerated: Accelerated programs are offered at a fast pace that condenses the time to completion. Students typically take enough credits aimed at completing the program in a year or two.

Evening/Weekend: ​Courses meet on the UW–Madison campus only in evenings and/or on weekends to accommodate typical business schedules.  Students have the advantages of face-to-face courses with the flexibility to keep work and other life commitments.

Face-to-Face: Courses typically meet during weekdays on the UW-Madison Campus.

Hybrid: These programs combine face-to-face and online learning formats.  Contact the program for more specific information.

Online: These programs are offered 100% online.  Some programs may require an on-campus orientation or residency experience, but the courses will be facilitated in an online format.

CURRICULAR REQUIREMENTS

Minimum Credit Requirement 30 credits
Minimum Residence Credit Requirement 16 credits
Minimum Graduate Coursework Requirement 15 credits (50% of 30 credits) must be graduate-level coursework. Details can be found in the Graduate School’s policy: https://policy.wisc.edu/library/UW-1244
Overall Graduate GPA Requirement 3.00 GPA required.
This program follows the Graduate School's policy: https://policy.wisc.edu/library/UW-1203.
Other Grade Requirements A grade of B or better must be received in any course used to fulfill the required and elective course requirements.
Assessments and Examinations Students must pass a competency test containing both a written and an oral component, demonstrating that they have the potential to be a practicing statistician.
Language Requirements No language requirements.

Required COURSES

Required Courses:
STAT 609 Mathematical Statistics I3
or STAT/​MATH  709 Mathematical Statistics
STAT 610 Introduction to Statistical Inference4
or STAT/​MATH  710 Mathematical Statistics
STAT 849 Theory and Application of Regression and Analysis of Variance I3
STAT 850 Theory and Application of Regression and Analysis of Variance II3
STAT 998 Statistical Consulting3
Select 6 or more credits of Statistics courses 600 or higher 1
Must include 6 elective credits in:
STAT/​B M I  641 Statistical Methods for Clinical Trials3
And
STAT/​B M I  642 Statistical Methods for Epidemiology3
or STAT/​B M I  741 Survival Analysis Theory and Methods
or STAT/​B M I  877 Statistical Methods for Molecular Biology
The following will also be allowed to count toward the 30-credit minimum for the master's degree (with permission of the Director of Graduate Studies)
Up to 6 credits from Statistics Courses Numbered:6
R for Statistics I
R for Statistics II
R for Statistics III
Introduction to Time Series
Introductory Nonparametric Statistics
An Introduction to Sample Survey Theory and Methods
Applied Categorical Data Analysis
Data Science with R
Classification and Regression Trees
Introduction to Machine Learning and Statistical Pattern Classification
Introduction to Deep Learning and Generative Models
Applied Multivariate Analysis
Financial Statistics
Introduction to Computational Statistics
Introduction to Combinatorics
Special Topics in Statistics
Linear Optimization
Statistical Methods for Spatial Data
Courses that cover the same or similar topic at the undergraduate- and graduate-level may both be used towards the MS requirements. If both courses are to be used, the undergraduate level course must be completed first for both courses to be counted. Otherwise, only the graduate level course will be counted. Please note that this policy does not preclude students from taking just the undergraduate or just the graduate version of a topic. These combinations would include STAT 349 Introduction to Time Series and STAT 701 Applied Time Series Analysis, Forecasting and Control I; STAT 351 Introductory Nonparametric Statistics and STAT 809 Non Parametric Statistics; STAT 456 Applied Multivariate Analysis and STAT 760 Multivariate Analysis I; STAT 443 Classification and Regression Trees and STAT 761 Decision Trees for Multivariate Analysis; STAT 451 Introduction to Machine Learning and Statistical Pattern Classification and STAT 615 Statistical Learning; and STAT/​COMP SCI  471 Introduction to Computational Statistics and STAT 771 Statistical Computing. This will also apply to special topics courses that have similar topics between the undergraduate and graduate level.
Up to 6 credits of graduate courses outside of STAT in consultation with advisor.0-6
Up to 6 credits of STAT 699 in consultation with advisor.0-6
Total Credits30
1

 Courses that do not count in this requirement are: STAT 601 Statistical Methods I, STAT 602 Statistical Methods IISTAT 609 Mathematical Statistics I, STAT 610 Introduction to Statistical Inference, STAT 628 Data Science Practicum, STAT 678 Introduction to Statistical ConsultingSTAT 699 Directed Study, STAT/​MATH  709 Mathematical Statistics, STAT/​MATH  710 Mathematical Statistics, STAT 849 Theory and Application of Regression and Analysis of Variance I, STAT 850 Theory and Application of Regression and Analysis of Variance II, or STAT 998 Statistical Consulting

Graduate School Policies

The Graduate School’s Academic Policies and Procedures provide essential information regarding general university policies. Program authority to set degree policies beyond the minimum required by the Graduate School lies with the degree program faculty. Policies set by the academic degree program can be found below.

Named Option-Specific Policies

Prior Coursework

Graduate Work from Other Institutions

With program approval, students are allowed to count no more than 9 credits of graduate coursework from other institutions toward the graduate degree credit and graduate coursework (50%) requirements. Coursework earned five or more years prior to admission to a master’s degree is not allowed to satisfy requirements.

UW–Madison Undergraduate

With program approval, up to 6 statistics credits from a UW–Madison undergraduate degree at the 600 level or above are allowed to count toward minimum graduate degree credits. Coursework earned five or more years prior to admission to a master’s degree is not allowed to satisfy requirements.

UW–Madison University Special

With program approval, up to 15 statistics credits completed at UW–Madison while a University Special student at the 300 level or above are allowed to count toward minimum graduate degree and graduate residence credit requirements. Of these credits, those at the 700 level or above may also count toward the minimum graduate coursework (50%) requirement. Coursework earned five or more years prior to admission to a master’s degree is not allowed to satisfy requirements.

ProbatioN

Three consecutive reviews in which a student fails to meet the minimum criteria for satisfactory progress will result in the student being dropped from the program. Contact the program for more information.

ADVISOR / COMMITTEE

Students are required to meet with their advisor near the beginning of each semester to discuss course selection and progress.

CREDITS PER TERM ALLOWED

15 credits

Time Limits

The competency test must be passed within six semesters after entering the department.

grievances and appeals

These resources may be helpful in addressing your concerns:

Students should contact the department chair or program director with questions about grievances. They may also contact the L&S Academic Divisional Associate Deans, the L&S Associate Dean for Teaching and Learning Administration, or the L&S Director of Human Resources.

Other

Students pursuing the general statistics and biostatistics options are considered for department financial support and may seek a dual degree if desired.

Graduate School Resources

Take advantage of the Graduate School's professional development resources to build skills, thrive academically, and launch your career. 

Faculty: 

Cecile Ane, Professor

Joshua Cape, Assistant Professor 

Richard Chappell, Professor 

Peter Chien, Professor

Jessi Cisewski-Kehe, Assistant Professor

Deshpande, Sameer, Assistant Professor

Nicolas Garcia Trillos, Assistant Professor

Yinqiu He, Assistant Professor

Hyunseung Kang, Associate Professor

Sunduz Keles, Professor 

Bret Larget, Professor

Keith Levin, Assistant Professor

Wei-Yin Loh, Professor 

Michael Newton, Professor 

Vivak Patel, Assistant Professor

Alejandra Quintos, Assistant Professor

Garvesh Raskutti, Associate Professor

Karl Rohe, Professor

Kris Sankaran, Assistant Professor

Jun Shao, Professor 

Miaoyan Wang, Assistant Professor

Yahzen Wang (chair), Professor

Brian Yandell, Professor 

Chunming Zhang, Professor 

Yiqiao Zhong, Assistant Professor

Jun Zhu, Professor