Several long-standing empirical laws in geophysics have recently come under scrutiny, with emerging evidence suggesting that some may be based on misinterpretations of seismic data. These developments have been facilitated by the application of Exploratory Data Analysis (EDA), a statistical approach that emphasizes data-driven discovery over model-driven assumptions. This tutorial review introduces EDA as a practical and reproducible framework for seismic data analysis using the R programming environment. Through selected case studies, I demonstrate how EDA can reveal overlooked patterns, challenge conventional models, and offer new insights into earthquake behavior. The article also outlines key methodological tools, including Principal Component Analysis (PCA) and three-dimensional visualization, and discusses ongoing challenges and future directions for integrating EDA into mainstream seismological research.
Tomokazu Konishi (Fri,) studied this question.