EARTH 468
Data Analysis, Inference, and Estimation
This course introduces students to methods for the statistical description of data and their uncertainties, and the inference and estimation of indirect information. Emphasis is placed on conceptual understanding and practical application. Topics include error propagation, cluster analysis, Markov Chain Monte Carlo, least squares regression, robust regression, and model selection.
Topics
- error propagation
- cluster analysis
- Markov Chain Monte Carlo
- least squares regression
- robust regression
- and model selection
Topics explicitly listed in official catalogue description
Prerequisites & course information
MATH 115 or graduate standing. (Prerequisites enforced at registration.) Knowledge of, or willingness to learn, a programming language (e.g., Matlab, Mathematica). (3). (BS). (QR/2). May not be repeated for credit.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Data Analysis, Inference, and Estimation · 3 · Graduate credit