Students with a minor in Statistics will receive training in statistical methods, tailored to the aspect of statistics that they choose to emphasize. The minor has 12 credits of electives, giving lots of flexibility in course choices. Statistical skills are in demand across a wide range of disciplines. A minor in statistics is a valuable complement to many majors in the physical, biological, Earth, social and human sciences. Statistical skills are also in high demand in most private industries and government organizations.
If you are interested a minor in Statistics, please see our advising page or contact our department at stats@stat.colostate.edu.
Effective Spring 2026
Students must satisfactorily complete the total credits required for the minor. Minors and interdisciplinary minors require 12 or more upper-division (300- to 400-level) credits.
Additional coursework may be required due to prerequisites.
A minimum grade of C must be achieved in all STAT courses required for the minor in statistics.
| Code | Title | Credits |
|---|---|---|
| Introductory Course: Select either Group A or Group B below | 3-4 | |
| Group A, Take one of the following: | ||
| Introduction to Applied Statistical Methods | ||
| Introduction to Biostatistics | ||
| Intro to Theory and Practice of Statistics | ||
| Or Group B, Take each of the following: | ||
| General Statistics (GT-MA1) (((STAT 201 OR STAT 204) AND STAT 302A) should be an option for the introductory course) | ||
or STAT 204 | Statistics With Business Applications (GT-MA1) | |
| Statistics Supplement: General Applications | ||
| STAT 158 | Introduction to R Programming | 1 |
| STAT 341 | Statistical Data Analysis I | 3 |
| STAT 342 | Statistical Data Analysis II | 3 |
| STAT/DSCI or Outside Electives (select at least 6 credits from STAT/DSCI list – see lists below) | 12 | |
| Program Total Credits: | 22-23 | |
Statistics/Data Science Electives
| Code | Title | Credits |
|---|---|---|
| DSCI 335 | Inferential Reasoning in Data Analysis | 3 |
| DSCI 336 | Data Graphics and Visualization | 1 |
| DSCI 445 | Statistical Machine Learning | 3 |
| STAT 258 | Advanced R Programming | 2 |
| STAT 305 | Sampling Techniques | 3 |
| STAT 331 | Intermediate Applied Statistical Methods | 3 |
| STAT 351 | Sports Statistics and Analytics I | 3 |
| STAT 400 | Statistical Computing | 3 |
| STAT 420 | Probability and Mathematical Statistics I | 3 |
| STAT 421 | Introduction to Stochastic Processes | 3 |
| STAT 430 | Probability and Mathematical Statistics II | 3 |
| STAT 440 | Bayesian Data Analysis | 3 |
| STAT 451 | Sports Statistics and Analytics II | 3 |
| STAT 460 | Applied Multivariate Analysis | 3 |
| STAT 472 | Statistical Research--Design, Data, Methods | 3 |
Outside Electives
| Code | Title | Credits |
|---|---|---|
| AB 415 | Agricultural Data Science | 3 |
| BIOM 422 | Quantitative Systems and Synthetic Biology | 3 |
| BIOM 431/ECE 431 | Biomedical Signal and Image Processing | 3 |
| BZ 350 | Molecular and General Genetics | 4 |
| BZ 360 | Bioinformatics and Genomics | 4 |
| CIS 230 | ||
| CIS 370 | Analytics and AI in Business | 3 |
| CS 220 | Discrete Structures and the Applications | 4 |
| CS 320 | Algorithms--Theory and Practice | 3 |
| CS 345 | Machine Learning Foundations and Practice | 3 |
| CS 420 | Introduction to Analysis of Algorithms | 4 |
| CS 445 | Introduction to Machine Learning | 4 |
| DSCI 235 | Data Wrangling | 2 |
| DSCI 320/MATH 320 | Optimization Methods in Data Science | 3 |
| DSCI 369 | Linear Algebra for Data Science | 4 |
| DSCI 473 | Introduction to Geometric Data Analysis | 2 |
| DSCI 475 | Topological Data Analysis | 2 |
| ECE 303/STAT 303 | Introduction to Communications Principles | 3 |
| ECE 311 | Linear System Analysis I | 3 |
| ECE 312 | Linear System Analysis II | 3 |
| ECON 335/AREC 335 | Introduction to Econometrics | 3 |
| ECON 435 | Intermediate Econometrics | 3 |
| ECON 436 | Economic Forecasting | 3 |
| ERHS 332 | Principles of Epidemiology | 3 |
| ERHS 430 | Human Disease and the Environment | 3 |
| ESS 330 | Quantitative Reasoning for Ecosystem Science | 3 |
| F 321 | Forest and Natural Resource Biometry | 3 |
| F 422 | Quantitative Methods in Forest Management | 3 |
| FW 370 | Design of Fish and Wildlife Projects | 3 |
| FW 401 | Fishery Science | 3 |
| FW 471 | Wildlife Data Collection and Analysis | 4 |
| FW 475 | Conservation Decision Making | 3 |
| HDFS 350 | Applied Research Methods | 3 |
| MATH 269 | Geometric Introduction to Linear Algebra | 2 |
| MATH 301 | Introduction to Combinatorial Theory | 3 |
| MATH 317 | Advanced Calculus of One Variable | 3 |
| MATH 331 | Introduction to Mathematical Modeling | 3 |
| MATH 340 | Intro to Ordinary Differential Equations | 4 |
| MATH 345 | Differential Equations | 4 |
| MATH 360 | Mathematics of Information Security | 3 |
| MATH 369 | Linear Algebra I | 3 |
| MATH 411 | Stochastic Calculus and Financial Mathematics | 3 |
| MATH 450 | Introduction to Numerical Analysis I | 3 |
| MECH 231 | Engineering Experimentation | 2 |
| MECH 417 | Control Systems | 3 |
| MGT 475 | International Business Management | 3 |
| MKT 450 | Marketing Analytics | 3 |
| NR 422 | GIS Applications in Natural Resource Management | 4 |
| PSY 317 | Social Psychology Laboratory | 2 |
| PSY 350 | Research Design and Analysis II | 3 |
| PSY 370 | Psychological Measurement and Testing | 3 |
| PSY 371 | Psychological Measurement and Testing Lab | 1 |
| SOC 314 | Applications of Quantitative Research | 3 |
| WR 418 | Land Use and Water Quality | 3 |