GEOL 5050 - 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:
Credit Hours: 5
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture, 2.0 laboratory
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:

An additional term paper will be assigned to the graduate students to enhance their knowledge and the application of the learned material to specific problems of interest to the student formation.
Graduate students are expected to perform at higher levels than their undergraduate colleagues. Their achievements and degree of intellectual sophistication should surpass that of the undergraduates.
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.