Machine Learning for Social and Behavioral Research
eBook - PDF

Machine Learning for Social and Behavioral Research

  1. 416 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Machine Learning for Social and Behavioral Research

About this book

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.
 

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Yes, you can access Machine Learning for Social and Behavioral Research by Ross Jacobucci,Kevin J. Grimm,Zhiyong Zhang in PDF and/or ePUB format, as well as other popular books in Sciences sociales & Statistiques pour les entreprises et l'économie. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title Page
  3. Series Page
  4. Title Page
  5. Copyright
  6. Series Editor’s Note
  7. Preface
  8. Contents
  9. Part I. Fundamental Concepts
  10. Part II. Algorithms for Univariate Outcomes
  11. Part III. Algorithms for Multivariate Outcomes
  12. Part IV. Alternative Data Types
  13. References
  14. Author Index
  15. Subject Index
  16. About the Authors