Statistics: Statistics & Data Science MS
Master of Science in Statistics
Is this program right for you?
The Master of Science in Statistics: Statistics and Data Science at UW–Madison combines a background in statistical theory, methods, and practice related to data science with the communication skills you need to use data effectively for planning and decision making.
- Flexible, accelerated program allows you to earn your degree in just three to four semesters
- UW–Madison’s Department of Statistics is on the cutting edge of Big Data and predictive analytics research, and we are constantly innovating the curriculum to keep up with the industry
- You have the opportunity to attend many data conferences throughout the year, allowing you to gain insights in the field and network with statistics and data science leaders
Education that works for you
The Master of Science in Statistics: Statistics and Data Science program gives you the skills to make sense of complex data to achieve organizational goals.
Program type
Master’s degree
Degree awarded
Master of Science in Statistics
Commitment
1-2 years
Tuition
$1,600 per credit
Format
Accelerated
Face-to-face
Credits
30 graduate credits
Admission terms
Program admits for fall and spring terms
Offered by
Department of Statistics
STEM opt eligible
Yes
Supports F-1 Visa
Yes
Learn moreApplication deadlines
Spring 2027
- Deadline: October 1, 2026
Fall 2027
- Deadline: February 15, 2027
Your questions, answered
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Admissions and events
Program requirements
Application materials required
There are no upcoming events at this time.
Results that work for you
Statistics: Statistics & Data Science MS
$105,800
Median market salary in 2021
Job titles
Top industries
Top employers
21.5%
Projected job growth from 2020-2030. Source: Lightcast™ 2022.
What you’ll learn
Strengthen your statistical foundation and gain data science experience through the Statistics: Statistics & Data Science MS program. Through a combination of in-depth coursework and practical training, you’ll master statistical methods and data science computing to tackle real-world data challenges.
- Statistical methods
- Statistical inference
- Data science computing
- Statistical learning
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