Minor in Statistics and Data Science
Statistics, the science of making inferences and decisions under uncertainty, is becoming increasingly relevant in the modern world due to the widespread availability of and access to unprecedented amounts of data and computational resources. Unlike classical statistics, the need to process and manage massive amounts of data has become a key feature of modern statistics. This aspect of managing and processing data is popularly referred to as “data science.”
Through seven required subjects, the Minor in Statistics and Data Science provides students with a working knowledge base in statistics, probability, and computation, along with an ability to perform data analysis.
| Foundation 1 | ||
| 6.100A & 6.100B | Introduction to Computer Science Programming in Python and Introduction to Computational Thinking and Data Science | 12 |
| Foundation 2 | ||
| Select one of the following: | 12 | |
| Engineering Mathematics: Linear Algebra and ODEs | ||
| Differential Equations | ||
| Linear Algebra | ||
| Statistics 1 | ||
| Select one of the following: 1 | 12 | |
| Probability and Causal Inference | ||
| Introduction to Probability | ||
| Statistics for Brain and Cognitive Science | ||
| Introduction to Statistical Methods in Economics | ||
| Applied Probability and Statistics | ||
| Statistics and Probability | ||
| Probability and Random Variables | ||
| Statistics 2 | ||
| Select one of the following: | 12 | |
| Econometric Data Science | ||
| Statistical Thinking and Data Analysis | ||
| Fundamentals of Statistics | ||
| Computation & Data Analysis | ||
| Select two of the following: | 24 | |
| Engineering Computation and Data Science | ||
| Numerical Computation for Mechanical Engineers | ||
| Introduction to Inference | ||
| Introduction to Machine Learning | ||
| Advances in Computer Vision | ||
| Computational Systems Biology: Deep Learning in the Life Sciences | ||
| Advanced Econometrics | ||
| Optimization Methods in Business Analytics | ||
| Computational Modeling and Data Analysis in Aerospace Engineering 2 | ||
| Matrix Methods in Data Analysis, Signal Processing, and Machine Learning | ||
| Topics in Mathematics with Applications in Finance 2 | ||
| Capstone Subject | ||
| IDS.012[J] | Statistics, Computation and Applications | 12 |
| Total Units | 84 | |
| 1 | Consult minor advisor about potential substitutions. |
| 2 | Subject has prerequisites that are outside of the program. |
A minimum of four subjects taken for the Statistics and Data Science Minor cannot also count toward a major or another minor.
See the Statistics and Data Science Minor webpage for additional information. Inquiries about the undergraduate program may be directed to the IDSS Academic Office.
