William Menke is a Professor of Earth and Environmental Sciences at Columbia University. His research focuses on the development of data analysis algorithms for time series analysis and imaging in the earth and environmental sciences and the application of these methods to volcanoes, earthquakes, and other natural hazards. He has thirty years of experience teaching data analysis methods to both undergraduates and graduate students. Relevant courses that he has taught include, at the undergraduate level, Environmental Data Analysis and The Earth System, and at the graduate level, Geophysical Inverse Theory, Quantitative Methods of Data Analysis, Geophysical Theory and Practical Seismology.
1. Data Analysis with MATLAB or Python 2. Systematic explorations of a new
dataset 3. Modeling observational noise with random variables 4. Linear
models as the foundation of data analysis 5. Least squares with prior
information 6. Detecting periodicities with Fourier analysis 7. Modeling
time-dependent behavior with filters 8. Undirected data analysis using
factors, empirical orthogonal functions and clusters 9. Detecting and
understanding correlations among data 10. Interpolation, Gaussian Process
Regression and Kriging 11. Approximate methods, including linearization and
artificial neural networks 12. Assessing the significance of results
