GEOSCIENCE DATA ANALYSIS
Introduction to the fundamentals of applied geoscience data analysis, focusing on solving practical problems using real real-world data. Covers applied data analysis topics that are essential across a wide range of geoscience fields, including geophysics, geochemistry, hydrogeology, structural geology, sedimentology, geochronology, glacial geology, and geomorphology. Covers the use of example geoscience data sets to display and describe data; calculate and propagate uncertainties; test hypotheses; fit functions to data with linear regression and multiple linear regression; account for artifactual and serial correlation; analyze time series and directional data; and design experiments to optimize collection of rock, soil, and water samples.
Prerequisites & course information
Requisites: MATH 222 or graduate/professional standing Course Designation: Core GenEd - Natural Science & Wellness + Lab Level - Intermediate L&S Credit - L&S Liberal Arts and Science Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Learning Outcomes: 1. Quantitatively describe and display data distributions in geoscience applications. Audience: Both Grad & Undergrad 2. Calculate and propagate uncertainties in geoscience data. Audience: Both Grad & Undergrad 3. Test hypotheses about geoscience data using central tendencies and uncertainties. Audience: Both Grad & Undergrad 4. Describe how linear regression works and use it to quantify trends and their uncertainties in geoscience data. Audience: Both Grad & Undergrad 5. Recognize and account for common pitfalls in applications of data analysis to the geosciences. Audience: Both Grad & Undergrad 6. Analyze time series and directional data across the geosciences. Audience: Both Grad & Undergrad 7. Design geoscience data collection for testing hypotheses. Audience: Graduate Learning Outcomes: 1. Quantitatively describe and display data distributions in geoscience applications. Audience: Both Grad & Undergrad 2. Calculate and propagate uncertainties in geoscience data. Audience: Both Grad & Undergrad 3. Test hypotheses about geoscience data using central tendencies and uncertainties. Audience: Both Grad & Undergrad 4. Describe how linear regression works and use it to quantify trends and their uncertainties in geoscience data. Audience: Both Grad & Undergrad 5. Recognize and account for common pitfalls in applications of data analysis to the geosciences. Audience: Both Grad & Undergrad 6. Analyze time series and directional data across the geosciences. Audience: Both Grad & Undergrad 7. Design geoscience data collection for testing hypotheses. Audience: Graduate
Sources
- Course catalogue ↗2026-2027