Summary
Object Oriented Data Analysis (OODA), as conceptualized by J. S. Marron and Ian L. Dryden, offers a transformative perspective on statistical analysis amid the complexity of modern data. As data increasingly assumes nontraditional forms—shapes, curves, images, and networks—classical statistical methods often fall short. OODA addresses this gap by reimagining the very objects of analysis, urging practitioners to adapt their methodologies to the data's intrinsic structure and geometry. The book provides both a theoretical foundation and a practical guide, making it essential for statisticians, data scientists, and analysts grappling with high-dimensional and non-Euclidean data.
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