A general track for students looking to apply statistical methods to a wide variety of fields.
Introductory Courses
These courses make up the introduction to the Statistics program, 5 credits.
- First year seminar (STAT 192)
- Introduction to R Programming (STAT 158)
- Culture and Coding: Python (CS 150B)
Statistics Core
These courses make up the core of the Statistics program, 18 credits.
- Statistics Theory and Practice (STAT 315)
- Data Analysis I and II (STAT 341 & STAT 342)
- Probability and Mathematics Statistics I and II (STAT 420 & STAT 430)
- Statistics Research Methods (STAT 472)
Math Core
These courses make up the math component of the Statistics Major, 11-12 credits.
- Math for Computational Science I and II (MATH 156 & MATH 256)
- Linear Algebra (DSCI/MATH 369)
- Intro to Math Reasoning (MATH 235)
Note: most students start at a lower level of math – students do not need to be ready for calculus in the first semester!
Applied Electives:
- DSCI 335: Inferential Reasoning in Data
- STAT 305: Sampling Techniques
- STAT 331: Intermediate Applied Statistical Methods
- DSCI 445: Statistical Machine Learning
- STAT 440: Bayesian Data Analysis
Many students will add a minor in an area of interest – ask your advisor about this option!
Please contact the undergraduate advisor at elizabeth.montgomery@
