Chapter 18 deals with statistical methods, which are mathematical tools that can help aggregate, present and explore complex datasets from various sources. These methods can be very useful for understanding interactions, dependencies and relationships between social and ecological variables. The chapter discusses descriptive statistics, regression models, multivariate regression analysis, group comparison, clustering and non-metric dimensional scaling, principal component analysis, redundancy analysis, canonical correspondence analysis, factor analysis, multiple correspondence analysis, and time series analysis. It goes on to discuss the types of social-ecological systems (SES) problems and research questions commonly addressed by this set of methods, as well as their limitations, resource implications and new emerging research directions. The chapter also includes an in-depth case study showcasing the application of statistical analyses, and suggested further readings on these methods.