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This book is an innovative resource designed to bridge the gap between traditional psychological research methods and contemporary data science techniques. This book provides a comprehensive introduction to using Python for analyzing psychological data, enabling researchers, educators, and students to harness the analytical power of data science within their work. The volume is structured into four parts, encompassing programming skills, data preparation, advanced data processing, and the interpretation of results, each reinforced with practical examples and case studies. The content starts with the basics of Python programming, tailored specifically for psychological research applications. It then progresses to the sophisticated analysis of psychological data using statistical models, machine learning, and artificial intelligence, with a strong focus on Python's capabilities in these areas. This includes detailed discussions on Confirmatory Factor Analysis, machine learning algorithms like SVMs, and innovative techniques such as metaheuristics and simulations. This book is particularly timely as psychological research becomes increasingly data-driven, necessitating a deeper…

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