Covers probabilistic concepts and techniques that are useful for
environmental data analysis. The topics include: random variables; hypothesis
testing; linear regression, analysis of trends; space/time domain analysis; simulation of
random fields; Markovian processes; derived distributions; and stochastic differential
equations. Problem sets emphasize environmental applications. 3 Engineering
Design Points.
Prerequisites: 1.010 (Uncertainty in Engineering) or equivalent
Graduate (Fall)
3-0-9 H-LEVEL Grad Credit
Professor E.A.B. Eltahir
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