Below is an overview of Statistics (and Statistics-adjacent) courses, as well as some considerations for which students these courses may be best for. Requisites, course designations, and other course information can be found on the Statistics Course Guide.

## Avoid Duplicate Courses

Within the Data Science and Statistics majors, there are three course groups from which a student may count at most one course towards their major requirements. These are:

- Introduction to Linear Algebra (MATH 320, 340, 341, 375)
- Probability (STAT 309, 311, 431)
- Inference (STAT 310, 312)

If you have a question that is not answered on this webpage, you can email the Data Science major advisors at dsmajor@stat.wisc.edu, or the Statistics major advisor at advising@stat.wisc.edu.

## Gateway/Introductory Statistics Courses

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### STAT 240 Data Science Modeling I

STAT 240 is an intro course for those also interested in data science. This is the first course of the Data Science Modeling sequence. Students with an interest in the Data Science certificate or major should take this course. Statistical programming will be introduced and utilized: programming in the R language, as well as data management, analysis, and modeling.

### STAT 301 Introduction to Statistical Methods

STAT 301 is an intro course for those who are not excited about math. The course teaches statistics in less mathematical, more applied focused methods.

### STAT 324 Introductory Applied Statistics for Engineers

STAT 324 is an intro course for those who are interested in engineering or tech fields. The course requires calculus knowledge. Students will also be introduced to a statistical programming language.

### STAT 371 Introductory Applied Statistics for the Life Sciences

STAT 371 is an intro course for those who are interested in life sciences. The course requires knowledge of trigonometry and college algebra. Students will also be introduced to a statistical programming language.

## Probability Course Overviews

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### STAT/MATH 309 Introduction to Probability and Mathematical Statistics I

STAT 309 is an intensive calculus-based course that covers the fundamentals of Probability Theory and prepares students for the deep theory underlying statistical inference. A good fit for students looking for a rigorous treatment of probability, and statistical theory generally.

Intended for Math, Statistics, and Actuarial Science students. Recommended prerequisite course for STAT 310. Taught by the Statistics department.

### STAT/MATH 311 Introduction to Theory and Methods of Mathematical Statistics I

While still calculus-based, STAT 311 is a less mathematically intense alternative to STAT 309. Emphasis is placed on applications, largely from engineering. For this reason, it may be a preferred probability course for students less interested in theory.

Taught by the Statistics department.

### MATH/STAT 431 Introduction to the Theory of Probability

MATH 431 is a mathematically intensive probability course taught by the Math department. It is lecture only. Students will learn more connections to other areas of mathematics in this course, hence, this is a better fit for students who are very mathematically focused.

## Inference Courses

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### STAT/MATH 310 Introduction to Probability and Mathematical Statistics I

STAT 310 is a mathematically intensive course exploring the mathematical foundations of statistical inference. Intended for Statistics and Math majors, the course may be of interest to Data Science students (and others) seeking a deeper understanding of statistical procedures and their theoretical guarantees and justifications underpinnings.

Taught by the Statistics department.

### STAT/MATH 312 Introduction to Theory and Methods of Mathematical Statistics II

STAT 312 is a less mathematically intensive, more application-driven alternative to STAT 310. In it, the ideas behind statistical inference are explored using largely engineering-themed examples. The course is not recommended for Statistics and Math majors (for it doesn’t count toward either program’s requirements), and instead may be a more suitable choice students looking for a more practical and less theoretical approach to inference.

Taught by the Statistics department.

## Linear Algebra Courses

At most one linear algebra course is required for the Statistics and Data Science undergraduate majors. However, they are taught and administered by the Mathematics department. Please view their Courses webpage and scroll to the “linear algebra” section to view the differences between the four distinct intro-level linear algebra courses.

## Questions about courses and enrollment?

Make sure to check out the Courses & Enrollment FAQ page!