<p>Lecture, four hours; outside study, eight hours. Recommended preparation: some knowledge of MATLAB or Python. Covers methods for analyzing time series and spatial data within the context of environmental datasets (both air and water). Techniques covered include regressions, correlations, interpolations, spectral analysis, empirical orthogonal functions, clustering, and random forest. Focus on practical applications. Culminates in a final project where students apply these techniques to a research question of their choice. May be repeated once for credit. Letter grading.</p>

Civil and Environmental Engineering

Henry Samueli School of Engineering and Applied Science

C&EE 251E - Environmental Data Analysis

Environmental Data Analysis

Interpret the output of common data analysis techniques

Formulate a research question with consideration of data sources and analysis methods

Communicate findings clearly and justify their analytical approach

Apply a range of data analysis techniques effectively

Critically evaluate and provide constructive feedback on peers’ analyses

General Catalog

Environmental Data Analysis

C&EE 251E

4 units