Data Analysis in Water Sciences

4 credits

Covers fundamental topics related to data analysis, including statistical inference testing and error estimation, linear and quantile-based regression models, Monte Carlo simulation, time series analysis, Bayes theorem, and data visualization using modern computer techniques. Applications to water sciences, but techniques are applicable to any area. Prerequisite: IND E 315; either AMATH 301 or CSE 142; recommended: Basic stats and computer programming (or matlab) Offered: A.