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Dec 18, 2024
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GEOL 3050 - Statistical Methods in Geology
Statistics applied to geologic data including an introduction to probability, parametric statistics, comparison of populations, analysis of variance, non-parametric statistics, bivariate and multivariate statistics, identification of peak and background populations, directional data and circular statistics, analysis of transient data, and geographically distributed data. Use of statistical software, spreadsheets, and tools for geologic data analysis. Labs will use data sets from different areas of geology including hydrology, sedimentology, geophysics, structural geology, and paleontology.
Requisites: GEOL 1010 or 2020 and GEOL major and WARNING: not ISE 3040 or ISE 3200 or QBA 2010
Credit Hours: 4
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture, 2.0 laboratory
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes: - Be able to apply different non-parametric tests to geological data and find the statistical significance of correlations between two small data sets.
- Be able to apply statistical frequency distribution functions to the solution of geological problems and data sets.
- Be able to identify statistically the background and anomalous populations in a geological data set.
- Find the parameters of the normal distribution (e.g. mode, mean, standard deviation, variance) for geological data sets.
- Know how to analyze directional data sets and find the mean direction, circular dispersion, and its statistical significance.
- Know how to compare statistically various populations applying different statistical tests.
- Know how to find the best equation that describe the relationship between two data sets and its statistical significance.
- Know how to get multiple regression equations and their statistical meaning when several variables are involved.
- Know how to identify transient trends and cycles in geological data sets.
- Know how to identify uniformity, randomness, clustering, regularity, and anisotropy in geographically distributed data sets.
- Know how to obtain the best trend surface (linear, quadratic or cubic) and the residuals or anomalies in geographically distributed data, and their statistical significance.
- Understand how to apply Markov Chains to statigraphic data and identify cyclicity in the data.
- Understand the difference between parametric and non-parametric statistics.
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