EARTH 468 - Data Analysis and Model Estimation
Section: 001
Term: FA 2017
Subject: Earth and Environmental Sciences (EARTH)
Department: LSA Earth & Environmental Sciences
Requirements & Distribution:
BS, QR/2
Enforced Prerequisites:
MATH 115.
Advisory Prerequisites:
Knowledge of, or willingness to learn, a programming language (e.g., Matlab, Mathematica).
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Primary Instructor:

This course introduces Earth and physical science students to data analysis technques and methods for constraining model parameters. Emphasis is placed on learning conceptual approaches to data analysis and applying these approaches in homework and computer exercises. The course surveys common techniques such as inverse theory and model estimation, as well as direct search methods (monte carlo, neighborhood algorithms, etc.), Bayesian techniques, least squares for linear and non-linear models, principal component analysis, and Kalman filtering. The characterization and propagation of data errors, covariance, data correlation, evaluation of model fit, and other topics in data analysis will also be covered. Additional topics, such as multi-scale analysis and gradient based methods may be covered depending on time and student interest. Students will gain knowledge of available tools and confidence in their application through hands-on exercises. Grade will be determined based on homework and a course project.

EARTH 468 - Data Analysis and Model Estimation
Schedule Listing
001 (LEC)
MW 2:00PM - 3:00PM
002 (LAB)
M 4:00PM - 6:00PM
003 (LAB)
Tu 4:00PM - 6:00PM
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