Data, Models, and Uncertainty in the Natural Sciences

Undergraduate catalogue

This course is for students who want to turn observations into models and subsequently evaluate their uniqueness and uncertainty. Three main topics, taught on the chalkboard, are elementary statistics (inference), heuristic time series (Fourier) analysis, and model parameter estimation via matrix inverse methods. Prerequisites: MAT 201 and 202. Theory lectures and classroom Matlab instruction in alternating weeks. Two 90-minute lectures/classes.