Hardcover. Etat : new. Hardcover. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9781462552931

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Machine Learning for Social and Behavioral Research (Methodology in the Social Sciences Series)

Jacobucci, Ross; Grimm, Kevin J.; Zhang, Zhiyong

Edit� par The Guilford Press, 2023

ISBN 10 : 1462552935 ISBN 13 : 9781462552931

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Machine Learning for Social and Behavioral Research

Jacobucci, Ross; Grimm, Kevin J.; Zhang, Zhiyong

Edit� par The Guilford Press, 2023

ISBN 10 : 1462552935 ISBN 13 : 9781462552931

Neuf Couverture rigide

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Machine Learning for Social and Behavioral Research (Hardcover)

Ross Jacobucci

Edit� par Guilford Publications, New York, 2023

ISBN 10 : 1462552935 ISBN 13 : 9781462552931

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Vendeur : CitiRetail, Stevenage, Royaume-Uni

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Hardcover. Etat : new. Hardcover. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9781462552931

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Machine Learning for Social and Behavioral Research (Hardcover)

Ross Jacobucci

Edit� par Guilford Publications, New York, 2023

ISBN 10 : 1462552935 ISBN 13 : 9781462552931

Neuf Couverture rigide

Vendeur : AussieBookSeller, Truganina, VIC, Australie

�valuation du vendeur 3 sur 5 �toiles

Hardcover. Etat : new. Hardcover. Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples. This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N� de r�f. du vendeur 9781462552931

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Jacobucci, Ross; Grimm, Kevin J.; Zhang, Zhiyong

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