This book provides a comprehensive exploration of the theoretical and foundational principles, as well as the applicational aspects of spatial statistics and analysis using the latest, most up-to-date data. It functions as a one-stop standalone resource for both instructors and undergraduate and graduate students using spatial analysis in geography and other earth sciences, as well as public health, engineering, urban and regional planning, criminal justice, epidemiology, and social sciences. Additionally, Spatial Statistics and Analysis is also useful for postgraduate students, researchers, social science practitioners, policy makers, government organizations and those who wish to gain an insight into spatial data analysis. It begins with a clear introduction of the key terms and tools in spatial statistics. Following on from that, it progresses into scales of measurement in spatial analysis and using these to analyze data distributions. Through the provision of compelling hands-on exercises, the book navigates complex topics such as spatial dataset visualizations, spatial statistical relationships and correlation, point features distributions and point pattern analysis. From there, the book moves into areal features distributions and areal pattern analysis using global and local statistics as well as complex spatial patterns and geostatistical analysis. Lastly it delineates the theory of spatial error and uncertainty, and real-world application of Markov chains. This textbook incorporates supplementary resources in the form of instructional slides for teaching, key for lab activities, data sets and high-quality graphic illustrations for students and instructors.