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Building on the foundation established in volume 1 of Statistical Analysis Techniques, this second volume delves deeper into advanced statistical techniques, providing comprehensive guidance for students and researchers working with SPSS Statistical Software.
Making Statistics Work presents a synthesis of information theory and Bayesian inference that provides a consistent, powerful, and flexible framework for data inference, allowing for new approaches to many of the unresolved questions of statistics.
This Element interrogates the complex role of gender in shaping the sociolinguistic variable of UPTALK within Hong Kong English. It provides a holistic, nuanced... Læs mere
This textbook explores vital networks and relationships among geographies and cultures that shaped medieval societies. Designed for students... Læs mere
This handbook presents a novel approach to updated, authoritative accounts of research on the sociologies of food and drink.... Læs mere
This book provides a thorough understanding of accident data collection, analysis, and use of surrogate safety measures from vehicular and pedestrian point of view. It... Læs mere
This book examines the role of critical methodology in literacy and language practices.... Læs mere
The book integrates concepts from various disciplines, including quantum mechanics, algebra, and information theory, providing a comprehensive understanding of how these fields intersect and contribute to advances in coding theory and cryptography.
In a world where culture evolves at an unprecedented pace, Story Systems provides researchers, analysts, and strategists with a groundbreaking methodology for decoding cultural shifts through language.
Introduction to Hazard Analysis Methods: A Practical Guide to Identifying and Assess Risks in the Workplace, is for safety professionals, risk analysts, engineers, project managers, teachers and students of occupational safety and health.
This book sets out to reposition research from an intimidating academic ritual to a practical, intuitive process that anyone can engage with. It explains key research concepts using everyday language without oversimplifying them.
Bias and Beyond is anchored in a commitment to Diversity, Equity, and Inclusion (DEI), not only as aspirational values but as methodological imperatives that must inform every aspect of data practice.