This is a named option (formally documented sub-major) professional program in the Statistics MS. Data science is the study of extracting knowledge from data. Our MS Statistics: Statistics and Data Science option combines a background in statistical theory, methods and practice related to data science with communication skills to train a new generation of leaders who will use data effectively for planning and decision making.
Data science concepts enable students to translate vague questions about complex data into pragmatic analysis steps using statistical thinking. We build from basic methods that compare groups and relate measurements, to more complicated models that depend on the way data are gathered. In practice, planning and decision making involve choices about how to analyze data and communicate findings. These concepts will be grounded at key points with projects that involve real data and/or realistic simulated data.
Students may also be interested in the MS Data Science professional program, offered by the Department of Statistics in cooperation with Department of Computer Sciences. The MS Data Science program is designed for students who are primarily interested in entering the data science profession, and teaches key computational and statistical skills that may be applied to a variety of industries.
Admissions
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 | February 15 |
| Spring Deadline | October 1 |
| Summer Deadline | This program does not admit in the summer. |
| GRE (Graduate Record Examinations) | Not Required. |
| English Proficiency Test | Refer to the Graduate School: Minimum Requirements for Admission policy: https://policy.wisc.edu/library/UW-1241. |
| 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.
The MS Statistics: Statistics and Data Science program is intended for three types of applicants:
- MS Statistics: Statistics and Data Science for Visiting International Student Program (VISP) students
- Students from the Visiting International Student Program (Statistics VISP or Math VISP) who have completed some degree requirements at UW-Madison as Visiting International Student Program undergraduates. They may request transfer of up to 14 credits from their Visiting International Student Program coursework.
- MS Statistics: Statistics and 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: Statistics and 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: Statistics and Data Science students.
Requisites for Admission
Applicants admitted to the MS Statistics: Statistics and Data Science program are expected to have courses equivalent to the UW-Madison courses listed below.
| Code | Title | Credits |
|---|---|---|
| Calculus | ||
| 4 semesters of calculus: | ||
| MATH 221 | Calculus and Analytic Geometry 1 | 5 |
| MATH 222 | Calculus and Analytic Geometry 2 | 4 |
| MATH 234 | Calculus--Functions of Several Variables | 4 |
| MATH 421 | The Theory of Single Variable Calculus (or another advanced analysis course) | 3 |
| Linear Algebra | ||
| MATH 340 | Elementary Matrix and Linear Algebra | 3 |
| or MATH 345 | Linear Algebra and Optimization | |
| Highly Recommended | ||
| STAT 303 | R for Statistics I | 1 |
| STAT 304 | R for Statistics II | 1 |
| STAT/MATH 309 | Introduction to Probability and Mathematical Statistics I | 3 |
| STAT/MATH 310 | Introduction to Probability and Mathematical Statistics II | 3 |
Funding
Graduate School Resources
The Bursar’s Office provides information about tuition and fees associated with being a graduate student. 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 Information
Students enrolled in this program are not eligible to receive tuition remission from graduate assistantship appointments at this institution.
Additional information about funding and scholarships for MS Statistics: Statistics and Data Science is available on the program website.
Minimum Graduate School Requirements
Review the Graduate School minimum degree requirements and policies, 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
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 must be graduate-level coursework. Refer to the Graduate School: Minimum Graduate Coursework (50%) Requirement policy: https://policy.wisc.edu/library/UW-1244. |
| Overall Graduate GPA Requirement | 3.00 GPA required. Refer to the Graduate School: Grade Point Average (GPA) Requirement policy: https://policy.wisc.edu/library/UW-1203. |
| Other Grade Requirements | Students may only have one core course (STAT 601, STAT 610, or STAT 615) with a grade below B. |
| Assessments and Examinations | None. |
| Language Requirements | No language requirements. |
Required Courses
| Code | Title | Credits |
|---|---|---|
| Core | ||
| STAT 601 | Statistical Methods I 1 | 4 |
| STAT 610 | Introduction to Statistical Inference 1 | 4 |
| STAT 615 | Statistical Learning 1 | 3 |
| Professional Skills Courses | ||
| STAT 605 | Data Science Computing Project 1 | 3 |
| STAT 628 | Data Science Practicum 1 | 3 |
| or STAT 678 | Introduction to Statistical Consulting | |
| Electives | ||
| Students must complete 13 credits of electives. | 13 | |
| STAT Courses Numbered 600 or Above | ||
| At least 6 credits of STAT courses numbered 600 or above including the following: | ||
| Computing in Data Science and Statistics (At least 6 credits of STAT courses numbered 600 or above including the following:) | ||
| Mathematical Statistics I | ||
| Statistics in Human Genetics | ||
| 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 I | ||
| Mathematical Statistics II | ||
| 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 | ||
| Computational Statistics | ||
| Linear Randomized Algorithms for Data Science | ||
| Bayesian Statistics | ||
| Experimental Design I | ||
| Non Parametric Statistics | ||
| Empirical Processes and Semiparametric Inference | ||
| Nonparametric Statistics and Machine Learning Methods | ||
| Statistical Methods for Molecular Biology | ||
| Seminar | ||
| STAT Courses Numbered 300-599 | ||
| Students may count up to 3 credits of STAT electives numbered 300-599 including: | ||
| R for Statistics I | ||
| R for Statistics II | ||
| R for Statistics III | ||
| Introduction to Time Series | ||
| Introductory Nonparametric Statistics | ||
| Data Science Computing Project | ||
| An Introduction to Sample Survey Theory and Methods | ||
| Applied Categorical Data Analysis | ||
| Data Science with R | ||
| Statistical Data Visualization | ||
| 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 | ||
| Special Topics in Statistics | ||
| Statistical Methods for Spatial Data | ||
| Non-Departmental Course Numbered 500 or Above | ||
| Students may count up to 1 elective course (up to 4 credits) numbered 500 or above taught outside of STAT with advisor approval from the courses below. Students are not guaranteed a seat in an elective course taught from outside of the Statistics department. They must obtain departmental permission to enroll. | ||
| Introduction to Stochastic Processes | ||
| Introduction to Artificial Intelligence | ||
| Introduction to Algorithms | ||
| Introduction to Computer Networks | ||
| Nonlinear Optimization I | ||
| Remaining Electives | ||
| To satisfy the 13-credit elective minimum, students may also apply the following courses: | ||
| R for Statistics I | ||
| R for Statistics II | ||
| R for Statistics III | ||
| Internship Course in Comp Sci and Data Science (1 credit maximum allowed) | ||
| Professional Skills in Data Science | ||
| Directed Study (2 credits maximum allowed) | ||
| Total Credits | 30 | |
- 1
Students who are able to demonstrate equivalent prior coursework may request to substitute required course with a Statistics-taught course numbered 600 or above with advisor approval. Substitutions are not guaranteed and will be reviewed on a case-by-case basis.
Graduate and Undergraduate Courses with Similar Topics
Courses that cover the same or similar topic at the undergraduate- and graduate-level may both be used to fulfill the MS in Statistics and Data Science requirements, but if both courses are to be used, the undergraduate level course must be completed first. 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 and STAT 701, STAT 351 and STAT 809, STAT 405 and STAT 605, STAT 411 and STAT 732, STAT 456 and STAT 760, STAT 443 and STAT 761, STAT 451 and STAT 615, and STAT/COMP SCI 471 and STAT 771. This will also apply to special topics courses that have similar topics between the undergraduate and graduate level.
Other Policy
Students in this program may not take courses outside the prescribed curriculum without faculty advisor and program director approval. Students in this program cannot enroll concurrently in other undergraduate or graduate degree programs.
Graduate School Policies
The Graduate School’s Academic Policies and Procedures serve as the official document of record for Graduate School academic and administrative policies and procedures and are updated continuously. Note some policies redirect to entries in the official UW-Madison Policy Library. Programs may set more stringent policies than the Graduate School. Policies set by the academic degree program can be found below.
Named Option-Specific Policies
Prior Coursework
Graduate Credits Earned at Other Institutions
With program approval, students are allowed to transfer 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.
Undergraduate Credits Earned at Other Institutions or UW-Madison
With program approval, up to 7 credits from a UW–Madison undergraduate degree are allowed to transfer toward the minimum graduate degree credit requirement. Coursework earned five or more years prior to admission to a master’s degree is not allowed to satisfy requirements. This program does not accept undergraduate credits from other institutions.
Credits Earned as a Professional Student at UW-Madison (Law, Medicine, Pharmacy, and Veterinary careers)
Refer to the Graduate School: Transfer Credits for Prior Coursework policy.
Credits Earned as a University Special Student at UW–Madison
With program approval, up to 14 Statistics (STAT) credits completed at UW–Madison while a University Special student numbered 300 or above are allowed to transfer toward the minimum graduate degree credit requirement. Of these credits, those numbered 700 or above or are taken to meet the requirements of a capstone certificate and has the "Grad 50%" attribute may also transfer 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 credit maximum. Refer to the Graduate School: Maximum Credit Loads and Overload Requests policy.
Time Limits
Students are expected to complete the program in 2 semesters (if coming from the Statistics Visiting International Student Program program) or 3-4 semesters. Students who wish to pursue the program part time must receive permission from the program chair.
Grievances and Appeals
These resources may be helpful in addressing your concerns:
- Bias or Hate Reporting
- Graduate Assistantship Policies and Procedures
- Hostile and Intimidating Behavior Policies and Procedures
- Employee Assistance (for personal counseling and workplace consultation around communication and conflict involving graduate assistants and other employees, post-doctoral students, faculty and staff)
- Employee Disability Resource Office (for qualified employees or applicants with disabilities to have equal employment opportunities)
- Graduate School (for informal advice at any level of review and for official appeals of program/departmental or school/college grievance decisions)
- Office of Compliance (for class harassment and discrimination, including sexual harassment and sexual violence)
- Office Student Assistance and Support (OSAS) (for all students to seek grievance assistance and support)
- Office of Student Conduct and Community Standards (for conflicts involving students)
- Ombuds Office for Faculty and Staff (for employed graduate students and post-docs, as well as faculty and staff)
- Title IX (for concerns about discrimination)
L&S Policy for Graduate Student Academic Appeals
Graduate students have the right to appeal an academic decision related to an L&S graduate program if the student believes that the decision is inconsistent with published policy.
Academic decisions that may be appealed include:
- Dismissal from the graduate program
- Failure to pass a qualifying or preliminary examination
- Failure to achieve satisfactory academic progress
- Academic disciplinary action related to failure to meet professional conduct standards
Issues such as the following cannot be appealed using this process:
- A faculty member declining to serve as a graduate student’s advisor.
- Decisions regarding the student’s disciplinary knowledge, evaluation of the quality of work, or similar judgements. These are the domain of the department faculty.
- Course grades. These can be appealed instead using the L&S Policy for Grade Appeal.
- Incidents of bias or hate, hostile and intimidating behavior, or discrimination (Title IX, Office of Compliance). Direct these to the linked campus offices appropriate for the incident(s).
Appeal Process for Graduate Students
A graduate student wishing to appeal an academic decision must follow the process in the order listed below. Note time limits within each step.
- The student should first seek informal resolution, if possible, by discussing the concern with their academic advisor, the department’s Director of Graduate Studies, and/or the department chair.
- If the program has an appeal policy listed in their graduate program handbook, the student should follow the policy as written, including adhering to any indicated deadlines. In the absence of a specific departmental process, the chair or designee will be the reviewer and decision maker, and the student should submit a written appeal to the chair within 15 business days of the academic decision. The chair or designee will notify the student in writing of their decision.
- If the departmental process upholds the original decision, the graduate student may next initiate an appeal to L&S. To do so, the student must submit a written appeal to the L&S Assistant Dean for Graduate Student Academic Affairs within 15 business days of notification of the department’s decision.
- To the fullest extent possible, the written appeal should include, in a single document: a clear and concise statement of the academic decision being appealed, any relevant background on what led to the decision, the specific policies involved, the relief sought, any relevant documentation related to the departmental appeal, and the names and titles of any individuals contributing to or involved in the decision.
- The Assistant Dean will work with the Academic Associate Dean of the appropriate division to consider the appeal. They may seek additional information and/or meetings related to the case.
- The Assistant Dean and Academic Associate Dean will provide a written decision within 20 business days.
- If L&S upholds the original decision, the graduate student may appeal to the Graduate School. More information can be found on their website: Grievances and Appeals (see: Graduate School Appeal Process).
Other
Not applicable.
Professional Development
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 Statistics: Statistics and Data Science, MS 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.