Courses
The minor in Data Science & Statistics prepares students to address the challenges of collecting, understanding, and presenting structured and unstructured data from a variety of different domains and contexts.
The program takes an interdisciplinary approach built around five specific skills needed to achieve these goals:
- Developing proficiency in data-oriented programing
- Understanding probability theory and statistical inference
- Understanding which methods are appropriate for which kinds of data analysis
- Ability to identify and address the ethical and privacy concerns regarding data analysis, and
- Gaining experience applying techniques and presenting results within the context of an application domain.
Courses
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- DSST 189 Introduction to Statistical Modeling
- DSST 289 Introduction to Data Science
- DSST 310 Causal Inference
- DSST 311 Data Collection and Design
- DSST 312 Predictive Models
- DSST 329 Probability
- DSST 330 Mathematical Statistics
- DSST 331 Regression Theory and Applications
- DSST 389 Advanced Data Science
- DSST 390 Directed Independent Study
- DSST 395 Special Topics in Data Science & Statistics
- DSST 406 Summer Undergraduate Research