Statistics provides the reasoning and the methods for producing and understanding data; it is the science of learning from data. It includes designing experiments or sampling surveys for the collection of data, collecting the information, evaluating it, drawing conclusions, and presenting the results.
Statisticians work with people from other professional backgrounds to solve practical problems. Statisticians can provide crucial guidance in determining what information is reliable and which predictions can be trusted. This diversity of application is an exciting aspect of the field, and is one reason for continuing strong demand for well-trained statisticians.
Statistics Major
Nearly every field relies on statisticians and data analysts to manage, evaluate, and communicate data. CSU Statistics graduates are employed across a wide variety of industries for jobs in data and analytics, finance, and research.
Statistics Major Tracks
Students have the option to complete an undergraduate track as part of the Statistics major.
Selecting a track is optional. Here you will find the general requirements for a Statistics Major:
Introductory Courses
These courses make up the introduction to the Statistics program.
- 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.
- 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.
- Math for Computational Science I and II (MATH 156 & MATH 256)
- Linear Algebra (DSCI/MATH 369)
- Intro to Math Reasoning (MATH 235)
Note: many students start at a lower level of math – students do not need to be ready for calculus in the first semester!
Major Electives
These courses make up the remainder of the Statistics program, 15 credits.
- 300-level Statistics, Data Science, Computer Science, and/or Math classes (up to 9 credits)
- 400-level Statistics classes (at least 6 credits)
For full program details, including additional course options, please see the Major Checklist or CSU Catalog.
We love transfer students! Check here for more information, and contact the undergraduate advisor at elizabeth.montgomery@colostate.edu to discuss how your previous coursework can apply to our Statistics program.
Statistics Minor
Adding a statistics minor to your degree program can be a valuable asset to future employers – nearly every industry relies on statistics and data analysis!
Here you will find the requirements for a Statistics Minor:
Introductory Courses
These courses make up the introduction to the Statistics minor, 4-5 credits.
- R Programming (STAT 158)
- Introduction to Statistics (choose one option)
- General Statistics and Statistics Supplement (STAT 201 & STAT 302A)
- Statistics for Business and Statistics Supplement (STAT 204 & STAT 302A)
- Applied Statistics (STAT 301)
- Biostatistics (STAT 307)
- Statistics Theory and Practice (STAT 315)
Statistics Core
These courses make up the core of the Statistics minor, 6 credits.
- Data Analysis I (STAT 341)
- Data Analysis II (STAT 342)
Minor Electives
These courses make up the elective portion of the Statistics Minor, 12 credits.
- Statistics electives: choose at least 6 upper-level STAT credits
- Outside electives: choose up to 6 outside credits
- Options include classes from a variety of disciplines, including Biology, Computer Science, Economics, Natural Resources, Math, Engineering, and Psychology
For full program details, including additional course options, please see the Minor Checklist or CSU Catalog.
Please contact the undergraduate advisor at elizabeth.montgomery@
Certificate in Sports Statistics and Analysis
The Certificate in Sports Statistics and Analytics will provide students with the knowledge and skills needed to work in the expanding field of sports analytics. Students will be able to acquire sports data using data scraping techniques and use these sports data to create graphical visualizations, generate summary statistics, build probabilistic models, assess hypothesis using statistical methods, create and evaluate regression models, implement machine learning algorithms, and present research findings in person and on paper.
Here you will find the requirements for a Certificate in Sports Statistics and Analysis:
Certificate Prerequisites
These courses make up the prerequisites of the Sports Statistics and Analytics Certificate, 4 credits.
- R Programming (STAT 158)
- Introduction to Statistics (choose one option)
- General Statistics (STAT 201)
- Statistics for Business (STAT 204)
- Applied Statistics (STAT 301)
- Biostatistics (STAT 307)
- Statistics Theory and Practice (STAT 315)
Certificate Core
These courses make up the core of the Sports Statistics and Analytics Certificate, 6 credits.
- Sports Statistics and Analytics I (STAT 351)
- Sports Statistics and Analytics II (STAT 451)
Certificate Electives
These courses make up the elective portion of the Sports Statistics and Analytics Certificate, 3 credits.
- Statistics electives: choose 1 of the following STAT credits:
- Intermediate Applied Statistical Methods (STAT 331)
- Statistical Computing (STAT 400)
- Introduction to Stochastic Processes (STAT 421)
- Bayesian Data Analysis (STAT 440)
- Applied Multivariate Analysis (STAT 460)
For full program details, including additional course options, please see the CSU Catalog.
Please contact the undergraduate advisor at elizabeth.montgomery@
Student Success
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Outside the Classroom
Department News
Q&A with Statistics Alumna Ellie Martinez
CSU Alumna Ellie Martinez shares her experience as a statistics student and how her time at CSU has helped her post-grad.
Q&A with statistics alum Gabe Macklem
CSU Statistics alum Gabe Mackelm (’25) shares his experience at CSU and his passion for sports statistics.
The Tomoa Skip: CSU researchers analyze the new move that revolutionized speed climbing
CSU undergraduate computer science student Caleb Chou and Department of Statistics Assistant Professor Andee Kaplan recently published a paper in CHANCE exploring the efficiency of the Tomoa Skip, a controversial rock climbing shortcut.
Q&A with data science alum Austin Lackey
CNS Source sat down with Austin Lackey, a CSU alum (’24), to learn more about the CSU Data Science program.
