Geostatistics and Data Analysis
Explore basic frequentist and Bayesian probability and statistics, confidence and significance models, multivariate and spatial correlated features, feature engineering, spatial debiasing and estimation, stochastic simulation, uncertainty modeling, basic machine learning, and optimum decision making in the presence of uncertainty. Examine applications to spatial problems such as geology and subsurface resource development. Petroleum and Geosystems Engineering 337 and 338 may not both be counted. Three lecture hours a week for one semester.
Prerequisites & course information
Explore basic frequentist and Bayesian probability and statistics, confidence and significance models, multivariate and spatial correlated features, feature engineering, spatial debiasing and estimation, stochastic simulation, uncertainty modeling, basic machine learning, and optimum decision making in the presence of uncertainty. Examine applications to spatial problems such as geology and subsurface resource development. Petroleum and Geosystems Engineering 337 and 338 may not both be counted. Three lecture hours a week for one semester.
Sources
- Course catalogue ↗2026-2027