1.715 Environmental Data Analysis


Class Info

Covers probabilistic concepts and techniques that are useful for environmental data analysis. Topics include random variables, hypothesis testing, linear regression, analysis of trends, space-time domain analysis, frequency domain analysis, simulation of random fields, Markovian processes, derived distributions, and stochastic differential equations. Problem sets emphasize environmental applications.

This class has 1.010 as a prerequisite.

1.715 will not be offered this semester. It will be instructed by E. A. B. Eltahir.

This class counts for a total of 12 credits. This is a graduate-level class.

You can find more information at the Subjects site.

MIT 1.715 Environmental Data Analysis Related Textbooks
MIT 1.715 Environmental Data Analysis On The Web
Subjects
Tags
environmental engineering hydrology h-level

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