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The amount of data in our world has been exploding, and analyzing large data sets-so called big data-will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.
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Table of Contents

Foreword Richard Klimoski 1. Building Understanding of the Data Science Revolution and IO Psychology Eden B. King, Scott Tonidandel, Jose M. Cortina, & Alexis A. Fink Part I: Big Issues for Big Data Methods 2. Big Data Platform Jacqueline Ryan 3. Statistical Methods for Big Data: A Scenic Tour Frederick L. Oswald & Dan J. Putka 4. Twitter Analysis: Methods for Data Management and a Word Count Dictionary to Measure City-Level Job Satisfaction Ivan Hernandez, Daniel A. Newman, & Gahyun Jeon 5. Data Visualization Evan F. Sinar 6. Sensing Big Data: Multimodal Information Interfaces for Exploration of Large Data Sets Jeffrey Stanton Part II: Big Ideas for Big Data in Organization 7. Implications of the Big Data Movement for the Advancement I-O Science and Practice Dan J. Putka & Frederick L. Oswald 8. Big Data in Talent Selection and Assessment A. James Illingworth, Michael Lippstreu, & Anne-Sophie Deprez-Sims 9. Big Data in Turnover/Retention John P. Hausknecht & Huisi (Jessica) Li 10. Using Big Data to Advance the Science of Team Effectiveness Steve W. J. Kozlowski, Georgia T. Chao, Chu-Hsiang (Daisy) Chang, & Rosemarie Fernandez 11. Using Big Data to Create Diversity and Inclusion in Organizations Whitney Botsford Morgan, Eric Dunleavy, & Peter D. DeVries 12. How Big Data Matters Richard A. Guzzo

About the Author

Scott Tonidandel is Associate Professor, Department of Psychology, Davidson College, NC. He received his PhD in Industrial Organizational Psychology from Rice University in 2001. He teaches courses in Psychological Research, Design and Analysis, Research Methods and Issues in Psychology. His research includes issues related to computerized testing, and statistical and methodological issues. Eden B. King is Associate Professor of Industrial Organizational Psychology at George Mason University. She earned her PhD from Rice University in 2006. Her research is mostly in the area of diversity, inclusion, and women in business. She is currently the Associate Editor of the Journal of Management and the Journal of Business and Psychology. She is also on the Editorial Board of the Academy of Management Journal. Jose M. Cortina, Professor of Industrial Organizational Psychology at George Mason University, is President Elect of SIOP. He received his PhD in psychology from Michigan State University. He serves as Editor of the I-O research methods journal Organizational Research Methods. He has an outstanding publication record and a tremendously high level of visibility in this field.

Reviews

'This is an essential must-read book for any one interested in doing or being a consumer of big data. It is a brilliant collection of contributors and articles providing great clarity to a challenging and critical area. This is the exact book needed to help navigate the data science revolution.' - Steven G. Rogelberg, University of North Carolina, Charlotte, USA 'Many fields have embraced Big Data and have sought to exploit the potential benefits. The editorial team of this book has brought together a strong collection of chapters that explore the meaning and impact of Big Data on the field of I/O psychology. Despite a rapidly changing landscape, this book will certainly prove to be valuable resource.' - Ron Landis, Illinois Institute of Technology, USA

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