The Department of Applied Mathematics offers a minor in statistics and data science. Declaration of a minor is open to any undergraduate student enrolled at CU Boulder, regardless of college or school. For more information, see the university's minor requirements on the Policies & Requirements page.

The minor in statistics and data science was developed to provide in-depth training in data science, statistical methods and techniques well beyond the training usually received by science and engineering majors. The ability to understand, visualize and analyze data is becoming an increasingly important skill in many disparate fields. This minor offers undergraduate students from any major the opportunity to develop their statistical knowledge.


Prerequisites for the Statistics and Data Science minor are two semesters of calculus and computing experiences such as provided by APPM 1650 (preferred), CSCI 1300 or CHEN 1310. A student cannot earn both a minor in statistics and data science and a minor in applied mathematics with the probability and statistics emphasis.

Students may earn both a BS in Applied Mathematics and a minor in Statistics and Data Science. However, the 12 upper-division credits of statistics required for the minor may not be counted towards the 25 credits of upper-division applied math courses. The 12 upper-division credits of statistics may, however, count towards the 24 credits of Area of Application required for all applied math majors.


A minimum of 23 credits at the 2000 level and above is required. At least three APPM or STAT courses, two of which must be at the 3000 level or above, need to be taken on the Boulder campus. No more than nine credit hours may be applied from transfer work; of those nine, no more than six may be 3000 level or above.

Minimum Grades

A cumulative GPA of 2.00 or better is required in the courses that are used to satisfy the requirements for this minor. Each individual course that is counted towards these degree requirements must be passed with a grade of C- or better.

Required Courses and Credit Hours

Required Courses
APPM 2350Calculus 3 for Engineers4-5
or MATH 2400 Calculus 3
or APPM 2340 Calculus 3 for Statistics and Data Science
APPM 3310Matrix Methods and Applications3
STAT 2600Introduction to Data Science4
APPM 3570/STAT 3100Applied Probability3
STAT 3400Applied Regression3
Elective Courses
Select two of the following courses: 16
Stochastic Analysis for Finance
Data Assimilation in High Dimensional Dynamical Systems
Applied Deep Learning 1
and Applied Deep Learning 2
Advanced Statistical Modeling
Spatial Statistics
Theory of Machine Learning
High-Dimensional Probability for Data Science
Introduction to Mathematical Statistics
Introduction to Time Series
Markov Processes, Queues, and Monte Carlo Simulations
Markov Processes, Queues, and Monte Carlo Simulations
Random Graphs
Statistical Learning
Computational Bayesian Statistics
Total Credit Hours23-24