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This course introduces theory and practical application of statistical methods in spatial analysis. Statistical fundamentals will be introduced to expose students to descriptive and inferential methods in spatial statistics. Geostatistical fundamentals will also be covered to introduce methods (in particular, kriging) for modelling spatial and spatio-temporal phenomena. This course will provide working knowledge of theory and practice in spatial statistics and Geostatistics, and will serve as a primer to more advanced courses in spatial statistics and machine learning. Theoretical knowledge will be supplemented with real-world use cases through in-class projects and assignments. Throughout the course, students will be exposed to open-source statistics libraries in R, no previous programming knowledge will be assumed. Offered twice a year.