This is a named option, professional program in the Statistics M.S.
Graduate School Admissions
Graduate admissions is a two-step process between academic degree programs and the Graduate School. Applicants must meet requirements of both the program(s) and the Graduate School. Once you have researched the graduate program(s) you are interested in, apply online.
| Fall Deadline | March 1 |
| Spring Deadline | October 15 |
| Summer Deadline | This 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 |
Students with questions regarding the programs admission rules and standards should visit our application website (http://www.stat.wisc.edu/ms-degree-data-science-option-ms-ds).
The MS-Statistics: Data Science program is intended for three types of students:
- MS-Statistics: Data Science for VISP students: Students from the Visiting International Student Program (Stat VISP or Math VISP) who have completed some degree requirements at UW-Madison as VISP undergraduates. They may request transfer of up to 15 credits from their VISP coursework.
- MS-Statistics: Data Science for workforce students: Students coming with 5 or more years in the workforce who have worked extensively with data and are seeking a well-rounded training. Some students may be part-time students (6-8 credits per semester) if they remain in the workforce.
- MS-Statistics: Data Science for other general students: Students who have BS degrees or expected to obtain BS degrees prior to the first semester as MS-Statistics: Data Science students.
Requisites for Admission
Course Requirements - Prerequisite Courses
| Code | Title | Credits |
|---|---|---|
| Students admitted to the MS-Statistics: Data Science program are expected to have courses equivalent to the UW-Madison courses listed below. | ||
| STAT 303 | R for Statistics I | 1 |
| STAT 304 | R for Statistics II | 1 |
| 4 semesters of calculus: | ||
| Calculus and Analytic Geometry 1 | ||
| Calculus and Analytic Geometry 2 | ||
| Calculus--Functions of Several Variables | ||
| The Theory of Single Variable Calculus | ||
| MATH 340 | Elementary Matrix and Linear Algebra | 3 |
| It is highly recommended that students also have: | ||
| Introduction to Probability and Mathematical Statistics I | ||
| Introduction to Probability and Mathematical Statistics II | ||
Degree Requirements
Students are required to have completed their BS/BA degree prior to the first semester as a MS-Statistics: Data Science students.
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 processes related to funding.
Program Resources
The M.S. Statistics: Data Science option is unique and does not allow students to accept a tuition remitting assistantship, hold multiple positions that would result in tuition remission, or to be concurrently enrolled in another university program or enrolled in courses outside of the M.S. Statistics: Data Science curriculum—see here for more 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 | Yes |
Mode of Instruction Definitions
Evening/Weekend: These programs are offered in an evening and/or weekend format to accommodate working schedules. Enjoy the advantages of on-campus courses and personal connections, while keeping your day job. For more information about the meeting schedule of a specific program, contact the program. Online: These programs are offered primarily online. Many available online programs can be completed almost entirely online with all online programs offering at least 50 percent or more of the program work online. Some online programs have an on-campus component that is often designed to accommodate working schedules. Take advantage of the convenience of online learning while participating in a rich, interactive learning environment. For more information about the online nature of a specific program, contact the program. Hybrid: These programs have innovative curricula that combine on-campus and online formats. Most hybrid programs are completed on-campus with a partial or completely online semester. For more information about the hybrid schedule of a specific program, contact the program. Accelerated: These on-campus programs are offered in an accelerated format that allows you to complete your program in a condensed time-frame. Enjoy the advantages of on-campus courses with minimal disruption to your career. For more information about the accelerated nature of a specific program, contact the program. |
CURRICULAR REQUIREMENTS
| Minimum Credit Requirement | 30 credits |
| Minimum Residence Credit Requirement | 16 credits |
| Minimum Graduate Coursework Requirement | Half of degree coursework (15 credits out of 30 total credits) must be completed graduate-level coursework; courses with the Graduate Level Coursework attribute are identified and searchable in the university's Course Guide (https://registrar.wisc.edu/course-guide/). |
| Overall Graduate GPA Requirement | 3.00 GPA required. |
| 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 | None. |
| Language Requirements | No language requirements. |
Required COURSES
| Code | Title | Credits |
|---|---|---|
| Required Courses: | ||
| STAT 601 | Statistical Methods I | 4 |
| STAT 602 | Statistical Methods II | 4 |
| STAT 610 | Introduction to Statistical Inference | 4 |
| STAT 615 | Statistical Learning | 3 |
| Professional Skills Courses (6 credits minimum from the following courses): | 6 | |
| Data Science Computing Project | ||
| Professional Skills in Data Science | ||
| Data Science Practicum | ||
Or E P D professional competency courses or other courses approved by the MS-Statistics: Data Science program | ||
| Students may substite STAT 605 or STAT 615 with STAT 609 with advisor approval | ||
| 9 elective credits: | 9 | |
| Students may count up to 3 credits of Statistics undergraduate electives including: | ||
| Introduction to Time Series | ||
| Introductory Nonparametric Statistics | ||
| An Introduction to Sample Survey Theory and Methods | ||
| Applied Categorical Data Analysis | ||
| Applied Multivariate Analysis | ||
| Financial Statistics | ||
| Introduction to Computational Statistics | ||
| Special Topics in Statistics | ||
| Statistical Methods for Spatial Data | ||
| Students may count up to 3 credits of 600-level or above coursework taught outside of Statistics with advisor approval, including courses cross listed with Statistics but taught by other departments | ||
| Student must have at least 3 credits of coursework at the 600-level taught within Statistics including the following: | ||
| Statistical Methods for Clinical Trials | ||
| Statistical Methods for Epidemiology | ||
| Special Topics in Statistics (may be repeated with different topic titles) | ||
| Applied Time Series Analysis, Forecasting and Control I | ||
| Mathematical Statistics | ||
| Mathematical Statistics | ||
| Large Sample Theory of Statistical Inference | ||
| Survival Analysis Theory and Methods | ||
| Multivariate Analysis I | ||
| Decision Trees for Multivariate Analysis | ||
| Statistical Methods for Medical Image Analysis | ||
| Statistical Computing | ||
| Introduction to Bayesian Decision and Control I | ||
| Experimental Design I | ||
| Non Parametric Statistics | ||
| Sample Survey Theory and Method | ||
| Empirical Processes and Semiparametric Inference | ||
| Statistical Model Building and Learning | ||
| Nonparametric Statistics and Machine Learning Methods | ||
| Estimation of Functions from Data | ||
| Statistical Methods for Molecular Biology | ||
| Total Credits | 30 | |
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
Graduate Program Handbook
The Graduate Program Handbook is the repository for all of the program's policies and requirements.
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 7 statistics credits from a UW–Madison undergraduate degree 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
Students are required to follow all of the requirements listed in the program handbook for maintaining satisfactory academic program. In particular, students must maintain a 3.0 GPA and have a minimum grade of B for any course used to satisfy program requirements. Students who do not make satisfactory academic progress for multiple semesters may be dismissed from the program.
ADVISOR / COMMITTEE
Students are required to communicate with their advisor near the beginning of each semester to discuss course selection and progress.
CREDITS PER TERM ALLOWED
15 credits
Time Constraints
Students are expected to complete the program in 2 semesters (if coming from the Statistics VISP program) or 3-4 semesters. Students who wish to pursue the program part time must receive permission from the program chair.
Other
The MS-Statistics: Data Science option is unique and does not allow students to accept a tuition remitting assistantship, hold multiple positions that would result in tuition remission, or to be concurrently enrolled in another university program or enrolled in courses outside of the MS-Statistics: Data Science curriculum—see here for more details.
Graduate School Resources
Take advantage of the Graduate School's professional development resources to build skills, thrive academically, and launch your career.
Program Resources
Students in the M.S. Statistics: Data Science program are encouraged to participate in program specific professional development events and work directly, one-on-one, with advisors as well. Information about events and resources will be made available to currently enrolled students via email.