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EDS 222

Statistics for Environmental Data Science

Tamma Carleton

Units: 4


This course teaches a variety of statistical techniques commonly used to address and analyze environmental data sets and questions and will provide an introduction to foundational concepts of spatial and space-time dependency and associated impacts on inference, with simple models illustrating the impact of space-time dependence when analyzing data from environmental processes. Techniques include: applied regression methods for environmental data, time series methods, spatial distance weighting methods, spatial covariances, spatial prediction using kriging, and multivariate statistics.

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