Offered in the Spring Quarter. 5 Units.

Basic quantitative understanding of processes shaping Earth’s surface. In-depth evaluation of hillslope diffusion, mass wasting, sediment transport, and fluvial processes. Applications of quantitative methods are emphasized throughout class. Laboratory provides understanding of experimental, physical, and remote sensing data.

Instructor: Ganti
Prerequisite: Geog. 3B; or Earth Science 2
Recommended Preparation: Basic knowledge of MATLAB

Quantitative methods for the analysis of geographical data. Topics include spatial clustering, spatial auto- correlation, spatial regression, and introductory methods for analyzing point, area (lattice), and continuous data. Lab includes the use of statistical software for exploratory spatial data analysis.

This course will provide basic introduction to probability and statistics. We will cover a range of topics from descriptive to inferential statistics. This course will also provide a review of discrete and continuous probability distributions along with methods to fit these probability models to empirical data and assess the quality of these fits. We will focus on methods for hypothesis testing, placing confidence intervals on sample means, and analyzing the variance. Finally, this course will provide basic introduction to correlation and regression, and will provide introduction to spatial aspects of regression analysis. The weekly exercises will provide an opportunity for the application of the material covered in class to datasets.