{"product_id":"machine-learning-for-social-and-behavioral-research-9781462552931","title":"Machine Learning for Social and Behavioral Research","description":"\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides skills to analyze and report large, complex data sets using machine learning tools, with a focus on the interplay of statistical algorithm, data, and theory. It covers basic principles and methods for analyzing univariate and multivariate data, as well as text and social network data. End-of-chapter Computational Time and Resources sections include discussions of key R packages. \u003c\/blockquote\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 416 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 04 September 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Guilford Publications\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003eToday's social and behavioral researchers face a pressing challenge: how to effectively handle the vast amounts of data they collect? This book is designed to provide the necessary skills and knowledge to analyze and report large, complex data sets using machine learning tools. It offers a comprehensive approach, covering both the theoretical foundations and practical applications of machine learning in social and behavioral research.\u003cbr\u003e\u003cbr\u003eThe book begins by introducing the basic principles of machine learning and statistical analysis, providing a solid foundation for the subsequent chapters. It then delves into the practical aspects of data analysis, showcasing techniques such as data preprocessing, feature extraction, and model selection. Real-world examples, drawn from various domains, including psychology, education, and social sciences, help illustrate the concepts and techniques discussed.\u003cbr\u003e\u003cbr\u003eOne of the key strengths of the book is its emphasis on the interplay between statistical algorithms, data, and theory. It explains how different algorithms can be applied to different types of data and how to interpret the results obtained. The identification of heterogeneity, measurement error, regularization, and decision trees are also highlighted, as they are crucial factors in analyzing complex data sets.\u003cbr\u003e\u003cbr\u003eThe book covers a range of methods for analyzing univariate and multivariate data, including factor analysis, structural equation models, and mixed-effects models. It provides detailed explanations of these methods, along with practical examples and R programming scripts to facilitate the implementation of these techniques. Additionally, the book addresses the analysis of text and social network data, which are becoming increasingly important in modern research.\u003cbr\u003e\u003cbr\u003eTo assist readers in applying the concepts and techniques discussed, the book includes end-of-chapter Computational Time and Resources sections. These sections provide discussions of key R packages, which are widely used in machine learning and statistical analysis. The companion website offers additional R programming scripts and data for the book's examples, making it an invaluable resource for both students and practitioners.\u003cbr\u003e\u003cbr\u003eIn conclusion, this book is a valuable resource for social and behavioral researchers who want to leverage the power of machine learning to analyze and interpret large, complex data sets. It provides a comprehensive and practical approach, covering both basic principles and advanced techniques, and is accompanied by extensive resources to support learning and implementation. Whether you are a novice or an experienced researcher, this book will help you unlock the secrets of data analysis and make meaningful contributions to your field.\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1060g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 254 x 178 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781462552931\u003c\/p\u003e","brand":"Ross Jacobucci,Kevin J. Grimm,Zhiyong Zhang","offers":[{"title":"Hardback","offer_id":44584328102138,"sku":"9781462552931","price":80.91,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1695401081762_book.jpg?v=1695494864","url":"https:\/\/shulphink.com\/products\/machine-learning-for-social-and-behavioral-research-9781462552931","provider":"Shulph Ink","version":"1.0","type":"link"}