Big Data in Psychological Research PDF Download

Author: Sang Eun Woo
Publisher: American Psychological Association (APA)
ISBN: 9781433831676
Category : Psychology
Languages : en
Pages : 0

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Book Description
Big Data in Psychological Research provides an overview of big data theory, research design and analysis, collection methods, applications, ethical concerns, best practices, and future research directions for psychologists.

Author: Scott Tonidandel
Publisher: Routledge
ISBN: 1317702697
Category : Psychology
Languages : en
Pages : 321

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Book Description
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.

Author: Michael N. Jones
Publisher: Psychology Press
ISBN: 1315413566
Category : Computers
Languages : en
Pages : 384

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Book Description
The primary goal of this volume is to present cutting-edge examples of mining large and naturalistic datasets to discover important principles of cognition and to evaluate theories in a way that would not be possible without such scale. It explores techniques that have been underexploited by cognitive psychologists and explains how big data from numerous sources can inform researchers with different research interests and shed further light on how brain, cognition and behavior are interconnected. The book fills a major gap in the literature and has the potential to rapidly advance knowledge throughout the field. It is essential reading for any cognitive psychology researcher.

Author: Sandra Matz
Publisher: American Psychological Association (APA)
ISBN: 9781433836268
Category : Psychology
Languages : en
Pages : 320

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Book Description
The rapid advancements in technology, and our increasing interaction with it, have key implications for the field of psychology. The Psychology of Technology brings together research from different subdisciplines across psychology to address the ways in which technology and Big Data are changing how psychological research is conducted. It also examines how technology allows us to better understand human psychology. This text showcases cutting-edge research at the intersection of psychology and technology to provide an outlook into the future of psychological research in a tech-enabled world. The growing capabilities and reach of technology show no signs of abating, so it is critically important that psychology understand it and harness it effectively and ethically. Chapters offer fascinating and novel insights about the human condition using digital technologies as a window into human psychology, highlight the opportunities and challenges people face interacting with digital tech, and address the consequences of technology for individuals and societies. The intricacies of human-machine interaction, analyses of digital footprints, and "big data" approaches are investigated in detail.

Author: Chris Bradley
Publisher: John Wiley & Sons
ISBN: 1119487625
Category : Business & Economics
Languages : en
Pages : 256

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Book Description
Beat the odds with a bold strategy from McKinsey & Company "Every once in a while, a genuinely fresh approach to business strategy appears" —legendary business professor Richard Rumelt, UCLA McKinsey & Company's newest, most definitive, and most irreverent book on strategy—which thousands of executives are already using—is a must-read for all C-suite executives looking to create winning corporate strategies. Strategy Beyond the Hockey Stick is spearheading an empirical revolution in the field of strategy. Based on an extensive analysis of the key factors that drove the long-term performance of thousands of global companies, the book offers a ground-breaking formula that enables you to objectively assess your strategy's real odds of future success. "This book is fundamental. The principles laid out here, with compelling data, are a great way around the social pitfalls in strategy development." —Frans Van Houten, CEO, Royal Philips N.V. The authors have discovered that over a 10-year period, just 1 in 12 companies manage to jump from the middle tier of corporate performance—where 60% of companies reside, making very little economic profit—to the top quintile where 90% of global economic profit is made. This movement does not happen by magic—it depends on your company's current position, the trends it faces, and the big moves you make to give it the strongest chance of vaulting over the competition. This is not another strategy framework. Rather, Strategy Beyond the Hockey Stick shows, through empirical analysis and the experiences of dozens of companies that have successfully made multiple big moves, that to dramatically improve performance, you have to overcome incrementalism and corporate inertia. "A different kind of book—I couldn't put it down. Inspiring new insights on the facts of what it takes to move a company's performance, combined with practical advice on how to deal with real-life dynamics in management teams." —Jane Fraser, CEO, Citigroup Latin America

Author: Evanthia Lyons
Publisher: SAGE
ISBN: 0857024345
Category : Psychology
Languages : en
Pages : 306

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Book Description
Analysing Qualitative Data in Psychology equips students and researchers in psychology and the social sciences to carry out qualitative data analysis, focusing on four major methods (grounded theory, interpretative phenomenological analysis, discourse analysis and narrative analysis). Assuming no prior knowledge of qualitative research, chapters on the nature, assumptions and practicalities of each method are written by acknowledged experts. To help students and researchers make informed methodological choices about their own research the book addresses data collection and the writing up of research using each method, while providing a sustained comparison of the four methods, backed up with authoritative analyses using the different methods.

Author: Mike W. L. Cheung
Publisher:
ISBN: 9780889375512
Category : Big data
Languages : en
Pages : 80

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Book Description
Big data is becoming more prevalent in psychology and the behavioral sciences, and so are the methodological and statistical issues that arise from its use. Psychologists need to be equipped to deal with these. Big data can be generated in experimental studies where, for example, participants' physiological and psychological responses are tracked over time or where human brain imaging is employed. Observational data from websites such as Facebook, Twitter, and Google is also of increasing interest to psychologists. These sometimes huge data sets, which are often too large for standard computers and can also contain multiple types of data, bring with them challenging questions about data quality and the generalizability of the results as well as which statistical tools are suitable for analyzing them.The contributions in this volume explore these challenges, looking at the potential of applying machine learning techniques to big data in psychology as well as the split/analyze/meta-analyze (SAM) approach, which allows big data to be split up into smaller datasets so they can be analyzed with conventional multivariate techniques on standard computers. The issues of replicability, prediction accuracy, and combining types of data are also investigated.

Author: Bill Lubanovic
Publisher: "O'Reilly Media, Inc."
ISBN: 1492051322
Category : Computers
Languages : en
Pages : 634

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Book Description
Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.

Author: Ahmed Moustafa
Publisher: Academic Press
ISBN: 0128230029
Category : Medical
Languages : en
Pages : 386

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Book Description
Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. - Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders - Analyzes methods in using big data to treat psychiatric and neurological disorders - Describes the role machine learning can play in the analysis of big data - Demonstrates the various methods of gathering big data in medicine - Reviews how to apply big data to genetics

Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784

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Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.