BE-GY 6473
Applied Mathematics and Statistics for Biomedical Engineering
This course introduces applied mathematics and advanced statistical methods commonly encountered in biomedical engineering, while covering probability theory to bridge between mathematics and statistics. The topics include: generalized linear mixed models, discrete-time models, stochastic processes, elements of information theory, time-series analysis, causality analysis, and rudiments of probability theory. Beyond structured learning in class, students will work on the analysis of real datasets from the biomedical fields. | Prerequisite: Basic knowledge of calculus
Topics
- generalized linear mixed models
- discrete-time models
- stochastic processes
- elements of information theory
- time-series analysis
- causality analysis
- and rudiments of probability theory
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027