Data Science for the Geosciences

Review of mathematical and statistical concepts includes some foundational materials such as probability densities, Monte Carlo methods and Bayes’ rule are covered. We provide concept reviews that provide additional learning to the previous chapters. We aim to generate first an intuitive understanding of statistical concepts, then, if the student is interested, dive deeper into the mathemetical derivations. For example, principal component analysis can be taught by deriving the equations and making the link with eigenvalue decomposition of the covariance matrix. Instead, we start from simple two- and three-dimensional datasets and appeal to the student’s insight into the geometrical aspect: the study of an ellipse, and how we can transform it to a circle. This geometric aspect is explained without equations, but instead with plots and figures that appeal to intuition starting from geometry. In general, it is our experience that students in the geosciences retain much more practical knowledge when presented with material starting from case studies and intuitive reasoning.