Statistics Minor
The statistics minor is available for students who wish to gain a quantitative understanding of how to (a) measure uncertainty and (b) make good decisions on the basis of incomplete or imperfect information, and to apply these skills to their interests in another field. This minor could also be combined with a major in mathematics as preparation for a graduate degree in statistics or biostatistics.
Math placement is required for one or more of the foundational courses for this minor. For more information, please review the Math Placement website.
Course Requirements
Lower-Division Courses
Basic calculus sequence
| Either these courses | |
AM 11A | Mathematical Methods for Economists I | 5 |
AM 11B | Mathematical Methods for Economists II | 5 |
| or these courses | |
MATH 11A | Calculus with Applications | 5 |
MATH 11B | Calculus with Applications | 5 |
| or these courses | |
MATH 19A | Calculus for Science, Engineering, and Mathematics | 5 |
MATH 19B | Calculus for Science, Engineering, and Mathematics | 5 |
| or these courses | |
MATH 20A | Honors Calculus | 5 |
MATH 20B | Honors Calculus | 5 |
Plus one course from each of the following four categories
Statistical concepts
| Either this course | |
STAT 5 | Statistics | 5 |
| or these courses | |
STAT 7 | Statistical Methods for the Biological, Environmental, and Health Sciences | 5 |
STAT 7L | Statistical Methods for the Biological, Environmental, and Health Sciences Laboratory | 2 |
| or these courses | |
STAT 17 | Statistical Methods for Business and Economics | 5 |
STAT 17L | Statistical Methods for Business and Economics Laboratory | 2 |
Computer Programming
Take one of the following courses:
BME 160 | Research Programming in the Life Sciences | 6 |
CSE 20 | Beginning Programming in Python | 5 |
CSE 30 | Programming Abstractions: Python | 7 |
ASTR 119 | Introduction to Scientific Computing | 5 |
MATH 152 | Programming for Mathematics | 5 |
Linear Algebra
One of the following courses:
AM 10 | Mathematical Methods for Engineers I | 5 |
MATH 21 | Linear Algebra | 5 |
PHYS 116A | Mathematical Methods in Physics | 5 |
It is recommended that students also take AM 20 or MATH 24.
Multivariate Calculus
| Either this course | |
MATH 22 | Introduction to Calculus of Several Variables | 5 |
| or this course | |
AM 30 | Multivariate Calculus for Engineers | 5 |
| or these courses | |
MATH 23A | Vector Calculus | 5 |
MATH 23B | Vector Calculus | 5 |
Upper-Division Courses
Probability
One of the following "probability" courses:
STAT 131 | Introduction to Probability Theory | 5 |
STAT 203 | Introduction to Probability Theory | 5 |
CSE 107 | Probability and Statistics for Engineers | 5 |
Statistical Inference
STAT 132 | Classical and Bayesian Inference | 5 |
Computational Methods
One of the following courses:
AM 147 | Computational Methods and Applications | 5 |
MATH 148 | Numerical Analysis | 5 |
Plus two electives from the following list of courses
STAT 108 | Linear Regression | 5 |
STAT 204 | Introduction to Statistical Data Analysis | 5 |
STAT 206 | Applied Bayesian Statistics | 5 |
STAT 207 | Intermediate Bayesian Statistical Modeling | 5 |
STAT 208 | Linear Statistical Models | 5 |
BME 205 | Bioinformatics Models and Algorithms | 5 |
ECE 145 | Estimation and Introduction to Control of Stochastic Processes | 5 |
CSE 142 | Machine Learning | 5 |
ECON 104 | Is There Truth in Numbers: The Role of Statistics in Economics | 5 |
ECON 113 | Introduction to Econometrics | 5 |
ECON 114 | Advanced Quantitative Methods | 6 |
ECON 120 | Development Economics | 5 |
ECON 161B | Marketing Research | 5 |
ECON 190 | Senior Proseminar | 5 |
MATH 105A | Real Analysis | 5 |
MATH 105B | Real Analysis | 5 |
MATH 114 | Introduction to Financial Mathematics | 5 |
PSYC 181 | Psychological Data Analysis | 5 |
TIM 147 | Introduction to Data Mining for Business | 5 |
Note: Students planning graduate work in statistics are recommended to choose MATH 23A and MATH 23B, STAT 204 , STAT 205, and MATH 105A and MATH 105B.