The Statistical Science minor is designed to provide students in other disciplines with opportunities to extend their modeling and data analysis skills beyond introductory courses, to complement existing courses offered in other departments within their major, and to enhance such offerings to the benefit of students in terms of breadth of exposure to modern statistical thinking and computational statistical methods. The minor is flexible, so that students from most majors can find a path to the minor that serves their specific needs.
Prerequisite courses from mathematics: Calculus I [MATH 21 (31) or MATH 111L (31L) or equivalent] and Calculus II [MATH 122 (32) or MATH 112L (32L) or equivalent]. The skills developed and techniques explored in these courses are necessary for study of advanced statistical methods in the minor.
Required courses in Statistical Science: any five courses from
- STA 230 (104) [crosslisted as MATH 230 (135)] Probability: a full semester course in probability
- STA 250 (114) [crosslisted as MATH 342 (136)] Statistics: a mathematical statistics course covering likelihood and Bayesian methods
- STA 210 (121) Regression Analysis: methods of exploratory data analysis and model-based applied regression analysis
- STA 360 (122) Bayesian and Modern Statistics an introduction to modern, computationally intensive techniques for statistical analysis, emphasizing the Bayesian perspective
- STA 320 (130) Statistics of Causal Studies
- STA 321 (135) Statistics of Surveys
- STA 340 (140) Statistical Decision Analysis
- STA 470S (145S) Introduction to Statistical Consulting
- STA 471S (175) Computational Data Analysis
- STA 350S (180) Statistical Methods in Bioinformatics
- One course from STA 101 (101), STA 102 (102), STA 103 (102B), STA 111 (103), or STA 130 (113) may be counted toward the minor. Other electives must have pre-approval of the Director of Undergraduate Studies.)
See the Undergraduate Course Listings and Pathways for potential choices.