The mathematics named option programs allow students to develop a deep understanding of how the subject relates to other areas of human inquiry. The requirements for these programs feature mathematics courses with topics inspired by and commonly applied to problems in these associated fields. Though often paired with a second major in a related area, these programs function well alone and are suited to any mathematics student with a variety of interests. Students interested in a named option program are recommended to meet with an advisor to navigate the various plans and courses available to them. Advising information can be found on the BA or BS pages.

The named options do not support honors in the major.


The Mathematics for Statistical Analysis and Risk Assessment program requires 10 distinct courses for at least 30 credits as described below.  Note that while some courses may be used to fulfill more than one requirement it is still considered only a single course and may only contribute once to the total course count.  Finally, at most one course from each of the following groupings may be used to fulfill the minimum course and credit requirement (i.e.: minimum of ten courses and at least 30 credits):  Intro Linear Algebra (MATH 320MATH 340MATH 341MATH 375), Intro Differential Equations (MATH 319MATH 320 or MATH 376), and Intro Probability (MATH/​STAT  309 or MATH/​STAT  431).

Core Math Requirement (minimum of six distinct MATH courses for at least 18 credits) 1
Linear Algebra3-5
Linear Algebra
Linear Algebra and Differential Equations
Elementary Matrix and Linear Algebra
Topics in Multi-Variable Calculus and Linear Algebra
Probability (Complete at least one)3
Introduction to the Theory of Probability
Introduction to Probability and Mathematical Statistics I
Probability Theory
Statistics 13
Introduction to Probability and Mathematical Statistics II (Statistics)
Intermediate Mathematics Requirement (complete at least one)0-6
Applied Mathematical Analysis
and Applied Mathematical Analysis
Linear Algebra
Topics in Multi-Variable Calculus and Linear Algebra
The Theory of Single Variable Calculus
Advanced Mathematics Requirement (select one)3
Numerical Analysis
Analysis I
Probability Theory
Mathematical Methods in Data Science
Linear Algebra II
Electives to reach required six courses for at least 18 credits in MATH3-6
At least one elective must come from: 2
Numerical Linear Algebra
Numerical Analysis
Ordinary Differential Equations
Analysis I
Analysis II
Linear Optimization
Probability Theory
Mathematical Methods in Data Science
Linear Algebra II
Modern Algebra
Modern Algebra
Stochastic Methods for Biology
Data-Driven Dynamical Systems, Stochastic Modeling and Prediction
Analysis of Partial Differential Equations
Introduction to Fourier Analysis
Introduction to Measure and Integration
Introduction to Stochastic Processes
An Introduction to Brownian Motion and Stochastic Calculus
Remaining courses/credits may be selected from:
Techniques in Ordinary Differential Equations
Applied Mathematical Analysis
Applied Mathematical Analysis
Topics in Multi-Variable Calculus and Differential Equations
Applied Dynamical Systems, Chaos and Modeling
The Theory of Single Variable Calculus
Introduction to Combinatorial Optimization
Introduction to Cryptography
Applied Linear Algebra
Graphs and Networks in Data Science
Introduction to Number Theory
Introduction to Combinatorics
Statistics/Risk Requirement (Four Courses distinct from the above for at least 12 credits) 3
Select a distinct introduction course or sequence: 3-6
Actuarial Sciences:
Theory of Interest
Applied Regression Analysis
and Statistical Experimental Design
Data Science:
Data Science Modeling II
and Statistical Experimental Design
Select remaining courses/credits from: 46-14
Fundamentals of Long-Term Actuarial Modeling
Advanced Long-Term Actuarial Modeling
Fundamentals of Short-Term Actuarial Modeling
Advanced Short-Term Actuarial Modeling
Regression and Time Series for Actuaries
Health Analytics
Machine Learning for Business Analytics
Introduction to Time Series
Introductory Nonparametric Statistics
An Introduction to Sample Survey Theory and Methods
Applied Categorical Data Analysis
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
Linear Optimization
Statistical Methods for Spatial Data
Introduction to Stochastic Processes
Statistical Methods for Clinical Trials
Statistical Methods for Epidemiology
Data Driven Engineering Design
Total Credits30

Residence and Quality of Work

  • 2.000 GPA on all MATH courses and courses eligible for the major.5
  • 2.000 GPA on at least 15 credits of upper level credit in the major.6
  • 15 credits in MATH in the major taken on the UW-Madison campus.7



Students taking STAT 312 to satisfy the Statistics requirement will not be able to use this course towards the six courses/18 credits of MATH courses. 


This course must be distinct from the advanced mathematics requirement.


The courses which follow may have prerequisites outside of this program.


Any MATH course from the elective list above may be used in lieu of any of the following courses.


This includes any course with a MATH prefix (or cross-listed with MATH) regardless of its appearance in the tables above and any non-MATH course explicitly listed in the tables above.


This includes any MATH course (including those crosslisted with MATH) which are numbered 307 and above, regardless of its appearance in the tables above, as well as only those non-MATH course which appear in the tables above and have the advanced LAS attribute.


This includes any MATH course (and those crosslisted with MATH) numbered 307 and above.

Four-Year Plan

This Four-Year Plan is only one way a student may complete an L&S degree with this major. Many factors can affect student degree planning, including placement scores, credit for transferred courses, credits earned by examination, and individual scholarly interests. In addition, many students have commitments (e.g., athletics, honors, research, student organizations, study abroad, work and volunteer experiences) that necessitate they adjust their plans accordingly. Informed students engage in their own unique Wisconsin Experience by consulting their academic advisors, Guide, DARS, and Course Search & Enroll for assistance making and adjusting their plan.

In general, your four year plan in mathematics should be organized along the following sequence:

  1. Calculus
  2. Linear Algebra
  3. Required Intermediate level course
  4. Additional intermediate level courses as needed
  5. Required advanced level course
  6. Additional advanced level courses
MATH 2215MATH 2224
Literature Breadth3Literature Breadth3
Communication A3Ethnic Studies3
Foreign Language if required4Foreign Language (if required)4
 15 14
MATH 23414MATH Required Linear Algebra3
Humanities Breadth3MATH required Probability3
Communication B3Humanities Breadth3
Physical Science Breadth3Physical Science Breadth3
 16 15
MATH required Statistics3Required Intermediate MATH3
Data/Risk course3Data/Risk course3
Social Sciences Breadth3Social Science Breadth3
Biological Sciences Breadth3Biological Sciences Breadth3
 15 15
Required Advanced MATH3Advanced MATH Elective3
Data/Risk course3Data/Risk course3
Social Science Breadth3Social Science Breadth3
 15 15
Total Credits 120

Students should declare their major upon the successful completion of this course