As a complement to the Data Science program, which focuses on the applications of data analysis, the goal of the proposed statistics program is to acknowledge and train students in statistics as a rigorous field of mathematical sciences. The statistics minor is composed of six courses each targeting different learning objectives that allow students to build a deep appreciation and knowledge of the theoretical foundations that construct statistical methods and reasoning. The distribution format has been built into this program to allow for flexibility for students to customize student experience.
Requirements for the Statistics Minor (24 semester hours)
Area 1: Proficiency in R (4)
- DATA 151 Introduction to Data Science (4)
Area 2: Theoretic Basis for Statistics Distribution (4)
Area 3: Modeling Distribution (4)
Area 4: Calculus Distribution (4)
Area 5: Probability Theory Distribution (4)
Area 6: Electives (4)
- MATH 256 Differential Equations with Linear Algebra (4) or
- MATH 352 Linear Algebra (4) or
- ECON 350 Introduction to Econometrics and Forecasting (4) or
- BIOL 342 Biostatistics (4) or
- BIOL 347 Bioinformatics (4)
Statistics Faculty & Staff
- Kristen Gore, Assistant Professor of Data Science
- Hank Ibser, Clinical Associate Professor of Data Science
- Heather Kitada Smalley, Albaugh Assistant Professor of Statistics
- Elizabeth Silva Mendez, Computer and Data Science Program Coordinator