Advanced Environmental Data Analysis

Code:
EAS6490
Credits:
3.00
Lecture:
3.00
Research Areas:

This course is an advanced introduction to environmental data analysis and intended for first year graduate students. The goal of this class is to provide a deeper understanding of the theories and applications underlying the statistical analysis of environmental data, both in the space, time and spectral domain, and to provide the students with a hands-on experience. Ideally in the end of this class you will have developed a series of computer programming tool boxes and theoretical skills that should immediately be available for analyzing and modeling data in your own research. Although some preview knowledge of probability and statistics is required, a background review will be provided. Concepts and notation will be reintroduced as needed. In this class you will learn (a) how to combine models, which quantify statistical or dynamical relationships with observations (b) time series analysis, (c) forecasting and extrapolation, and (d) signal decomposition.