This is a named option within the Statistics MS. Find information about the traditional Statistics MS program requirements and policies here.
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 | 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) | 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 |
Applicants 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. Applicants are advised to undertake graduate work in statistics only if their undergraduate grades in mathematics were uniformly high.
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.
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 | 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 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 | 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
| Code | Title | Credits |
|---|---|---|
| Core | ||
| Students must complete the following courses. | ||
| STAT 849 | Advanced Statistical Methods | 4 |
| STAT 998 | Statistical Consulting | 3 |
| Mathematical Statistics I | ||
| Students must complete one of the following courses for at least 3 credits. | ||
| STAT 609 | Mathematical Statistics I | 3 |
| or STAT/MATH 709 | Mathematical Statistics I | |
| Mathematical Statistics II | ||
| Students must complete one of the following courses for 4 credits. | ||
| STAT 610 | Introduction to Statistical Inference | 4 |
| or STAT/MATH 710 | Mathematical Statistics II | |
| Methods | ||
| Students must complete 3 credits of methods. Refer to the "Methods Courses" table for courses that satisfy this requirement. | 3 | |
| Statistics Electives | ||
| Students must complete 6 credits of statistics electives. Refer to the "Statistics Electives Courses" table for courses that satisfy this requirement. Students cannot apply the same course towards both the methods requirement and statistics electives requirement. | 6 | |
| Additional Electives | ||
| Students must complete 7 credits of additional electives to meet the minimum credit requirement. Students may apply courses from the "Statistics Electives Courses" table to satisfy this requirement. Refer to the "Additional Electives Courses" table for more course options. Note: Students cannot apply the same course towards more than one of the category requirements. | 7 | |
| Total Credits | 30 | |
Methods Courses
| Code | Title | Credits |
|---|---|---|
| STAT 351 | Introductory Nonparametric Statistics | 3 |
| STAT 411 | An Introduction to Sample Survey Theory and Methods | 3 |
| STAT 421 | Applied Categorical Data Analysis | 3 |
| STAT 443 | Classification and Regression Trees | 3 |
| STAT 451 | Introduction to Machine Learning and Statistical Pattern Classification | 3 |
| STAT 453 | Introduction to Deep Learning and Generative Models | 3 |
| STAT 456 | Applied Multivariate Analysis | 3 |
| STAT 461 | Financial Statistics | 3 |
| STAT/B M I 542 | Introduction to Clinical Trials I | 3 |
| STAT 575 | Statistical Methods for Spatial Data | 3 |
| STAT/B M I 620 | Statistics in Human Genetics | 3 |
| STAT/B M I 641 | Statistical Methods for Clinical Trials | 3 |
| STAT/B M I 642 | Statistical Methods for Epidemiology | 3 |
| STAT/B M I 643 | Clinical Trial Design, Implementation, and Analysis | 3 |
| STAT/B M I 727 | Theory and Methods of Longitudinal Data Analysis | 3 |
| STAT/B M I 741 | Survival Analysis Theory and Methods | 3 |
| STAT 761 | Decision Trees for Multivariate Analysis | 3 |
| STAT/B M I 768 | Statistical Methods for Medical Image Analysis | 3 |
| STAT/ECON/GEN BUS 775 | Bayesian Statistics | 3 |
| STAT/MATH 803 | Experimental Design I | 3 |
| STAT/B M I 828 | Semiparametric Methods in Data Science | 3 |
| STAT 841 | Nonparametric Statistics and Machine Learning Methods | 3 |
| STAT/B M I 877 | Statistical Methods for Molecular Biology | 3 |
Statistics Electives Courses
| Code | Title | Credits |
|---|---|---|
| STAT/B M I 620 | Statistics in Human Genetics | 3 |
| STAT/B M I 641 | Statistical Methods for Clinical Trials | 3 |
| STAT/B M I 642 | Statistical Methods for Epidemiology | 3 |
| STAT/B M I 643 | Clinical Trial Design, Implementation, and Analysis | 3 |
| STAT 701 | Applied Time Series Analysis, Forecasting and Control I | 3 |
| STAT/COMP SCI/I SY E/MATH 726 | Nonlinear Optimization I | 3 |
| STAT/B M I 727 | Theory and Methods of Longitudinal Data Analysis | 3 |
| STAT 732 | Large Sample Theory of Statistical Inference | 3 |
| STAT/MATH 733 | Theory of Probability I | 3 |
| STAT/MATH 734 | Theory of Probability II | 3 |
| STAT/B M I 741 | Survival Analysis Theory and Methods | 3 |
| STAT 760 | Multivariate Analysis I | 3 |
| STAT 761 | Decision Trees for Multivariate Analysis | 3 |
| STAT/B M I 768 | Statistical Methods for Medical Image Analysis | 3 |
| STAT 772 | Linear Randomized Algorithms for Data Science | 3 |
| STAT/ECON/GEN BUS 775 | Bayesian Statistics | 3 |
| STAT 780 | Introduction to Quantum Data Science | 3 |
| STAT 801 | Advanced Financial Statistics | 3 |
| STAT/MATH 803 | Experimental Design I | 3 |
| STAT 809 | Non Parametric Statistics | 3 |
| STAT/B M I 828 | Semiparametric Methods in Data Science | 3 |
| STAT/MATH 833 | Topics in the Theory of Probability 1 | 3 |
| STAT 841 | Nonparametric Statistics and Machine Learning Methods | 3 |
| STAT/COMP SCI/E C E 861 | Theoretical Foundations of Machine Learning | 3 |
| STAT/B M I 877 | Statistical Methods for Molecular Biology | 3 |
| STAT/E C E/MATH 888 | Topics in Mathematical Data Science 1 | 1-3 |
| STAT 992 | Seminar 1 | 1-3 |
- 1
Students may not apply multiple special topics courses with the same topic title towards their degree.
Additional Electives Courses
| Code | Title | Credits |
|---|---|---|
| Statistics Courses Numbered 300-599 | ||
| Students may choose to apply up to 6 credits from the following courses. | ||
| STAT 303 | R for Statistics I | 1 |
| STAT 304 | R for Statistics II | 1 |
| STAT 305 | R for Statistics III | 1 |
| STAT 349 | Introduction to Time Series | 3 |
| STAT 351 | Introductory Nonparametric Statistics | 3 |
| STAT 411 | An Introduction to Sample Survey Theory and Methods | 3 |
| STAT 421 | Applied Categorical Data Analysis | 3 |
| STAT 433 | Data Science with R | 3 |
| STAT 443 | Classification and Regression Trees | 3 |
| STAT 451 | Introduction to Machine Learning and Statistical Pattern Classification | 3 |
| STAT 453 | Introduction to Deep Learning and Generative Models | 3 |
| STAT 456 | Applied Multivariate Analysis | 3 |
| STAT 461 | Financial Statistics | 3 |
| STAT/COMP SCI 471 | Introduction to Computational Statistics | 3 |
| STAT/COMP SCI/MATH 475 | Introduction to Combinatorics | 3 |
| STAT 479 | Special Topics in Statistics 1 | 1-3 |
| STAT/COMP SCI/I SY E/MATH 525 | Linear Optimization | 3 |
| STAT 575 | Statistical Methods for Spatial Data | 3 |
| Non-Departmental Courses | ||
| Students may choose to apply up to 6 credits of graduate courses outside of Statistics (STAT), chosen in consultation with advisor. | ||
| Directed Study | ||
| Students may choose to apply up to 6 credits from the following course, chosen in consultation with advisor. | ||
| STAT 699 | Directed Study | 1-6 |
- 1
Students may not apply multiple special topics courses with the same topic title towards their degree.
Additional Elective Courses Requirement: Statistics Courses Numbered 300-599
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 and STAT 701; STAT 351 and STAT 809; 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.
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
Refer to the Graduate School: Transfer Credits for Prior Coursework policy.
Undergraduate Credits Earned at Other Institutions or UW-Madison
With program approval, up to 6 Statistics (STAT) credits from a UW–Madison undergraduate degree numbered 600 or above may transfer toward minimum graduate degree credits. Coursework earned ten or more years prior to admission to a master’s degree is not allowed to satisfy requirements. Transfer credits from other institutions are not accepted.
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 taken to meet the requirements of a capstone certificate and has the "Grad 50%" attribute may also transfer for the minimum graduate coursework (50%) requirement. Coursework earned ten 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 credit maximum. Refer to the Graduate School: Maximum Credit Loads and Overload Requests policy.
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:
- 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
Students pursuing the general statistics and biostatistics options are considered for department financial support and may seek a dual degree if desired.
Professional Development
Graduate School Resources
Take advantage of the Graduate School's professional development resources to build skills, thrive academically, and launch your career.