Applied Electives for a Bachelor of Science
If you are pursuing a Bachelor of Science in Statistical Science, you must take one elective from in an applied field, such as as engineering, mathematics, natural sciences, or one of the quantitative social sciences. This course must contain statistical content above the level of STA 210 (Regression Analysis) and STA 250 (Statistics), and must be pre-approved by the Director of Undergraduate Studies (DUS).
Listed below are some external electives that have been approved in the past. You and your advisor can use this list as an inspiration in planning a pathway through the Statistical Science major. The list is ever-changing as departments change their existing course content or add or remove courses. Note that all external courses must be pre-approved by the DUS, including the ones listed below.
Also note that departments offer Special Topics courses that vary each semester that might be appropriate for meeting the external elective requirement for the major. Make sure to check out the department course listings for the latest update on their Special Topics offerings.
If you would like to take a course outside of this list that you believe might be a candidate for meeting the external elective requirement for the Statistical Science major, please email the DUS with name, number, and syllabus (outlining topics covered and textbook used, if any) of the course for pre-approval, prior to taking the course.
From Computer Science:
- COMPSCI 216 - Everything Data
- COMPSCI 270 - Intro to AI
- COMPSCI 290 - Data Science Competition (other topics courses approved on case-by-case basis)
- COMPSCI 316 - Intro to Database Systems
- COMPSCI 371D - Elements of Machine Learning
- COMPSCI 445/MATH 465 - Introduction to High Dimensional Data Analysis
- COMPSCI 527 - Computer Vision
- MATH 465 - Introduction to High Dimensional Data Analysis
- MATH 466 - Mathematics of Machine Learning
- MATH 531 - Basic Analysis (Recommended if you are thinking of applying for PhD programs)
- MATH 561 - Scientific Computing
- MATH 581 / ECON 673 - Mathematical Finance
- MATH 582/ECON 674 - Financial Derivatives
From Public Policy:
- PUBPOL 361S/PJMS 361S - Algorithms, Journalism, and the Public Interest
- PUBPOL 590 - Applied Big Data Science - Energy Data Analytics and Policy (other topics courses approved on case-by-case basis)
- BIOLOGY 311 - Systems Biology
From Global Health:
- GLHLTH 371/PSY 309 - Research Methods in Global Health
From Psychology and Neuroscience: