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Author : Anonim
Publisher : Unknown
Page : 168 pages
File Size : 52,6 Mb
Release : 1991
Category : Communication in the social sciences
ISBN : 1483325628
Author : Joan E. Sieber
Publisher : SAGE Publications
Page : 177 pages
File Size : 51,9 Mb
Release : 1991-02-12
Category : Education
ISBN : 9781452252919
Although major funding agencies now require social scientists to share their documented raw data, scientists have been reluctant to comply. The reasons include unwillingness to divulge all of the conditions under which the data were generated, cost in time and money, and the desire by social scientists to carry the research further themselves. Data sharing, however, promises to foster more open, cost-effective and cumulative research, and to improve the quality of methodology, data and inference. Sharing Social Science Data presents the major accomplishments of social scientists who have pioneered in data sharing, highlighting the advantages for social science. It also includes an examination of the reasons for data sharing, the specific sharing practices in various disciplines, the factors affecting the usefulness of shared data (documentation, archiving, and marketing), and individual and institutional concerns about data sharing. A timely examination, this cohesive and well written volume will interest graduate students and researchers in all areas of the social sciences. ". . .the chapters are thoughtful and well written, and they address many of the crucial issues faced by the social sciences in the 1990s. . . .anyone who wants to help shape the future of the social and behavioral sciences can benefit from giving this book at least a quick read." --Contemporary Psychology
Author : Louise Corti,Veerle Van den Eynden,Libby Bishop,Matthew Woollard
Publisher : SAGE
Page : 274 pages
File Size : 49,7 Mb
Release : 2014-02-04
Category : Social Science
ISBN : 9781446297735
Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today’s changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people’s research data, illustrated with six real-life case studies of data use.
Author : Anonim
Publisher : Amsterdam University Press
Page : 61 pages
File Size : 41,6 Mb
Release : 2010
Category : Social Science
ISBN : 9789085550396
This data guide takes readers through the cycle of social science research, from applying for a research grant, through conducting the data collection phase, and ultimately to preparing the data for deposit in archives or data repositories. An adaptation of the fourth edition of the Guide to Social Science Data Preparation and Archiving of 2009 by the Inter-University Consortium for Political and Social Research at the University of Michigan, this publication will help researchers to manage, document, and archive their data and to think broadly about which types of digital content should be deposited in such an archive.
Author : Anol Bhattacherjee
Publisher : CreateSpace
Page : 156 pages
File Size : 46,7 Mb
Release : 2012-04-01
Category : Science
ISBN : 1475146124
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Author : Elena Llaudet,Kosuke Imai
Publisher : Princeton University Press
Page : 256 pages
File Size : 55,6 Mb
Release : 2022-11-29
Category : Computers
ISBN : 9780691199436
"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--
Author : Douglas Bors
Publisher : SAGE
Page : 1115 pages
File Size : 52,8 Mb
Release : 2018-01-08
Category : Social Science
ISBN : 9781526422309
′This book fosters in-depth understanding of the logic underpinning the most common statistical tests within the behavioural sciences. By emphasising the shared ground between these tests, the author provides crucial scaffolding for students as they embark upon their research journey.′ —Ruth Horry, Psychology, Swansea University ′This unique text presents the conceptual underpinnings of statistics as well as the computation and application of statistics to real-life situations--a combination rarely covered in one book. A must-have for students learning statistical techniques and a go-to handbook for experienced researchers.′ —Barbra Teater, Social Work, College of Staten Island, City University of New York Accessible, engaging, and informative, this book will help any social science student approach statistics with confidence. With a well-paced and well-judged integrated approach rather than a simple linear trajectory, this book progresses at a realistic speed that matches the pace at which statistics novices actually learn. Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows students not only how to apply newfound knowledge using IBM SPSS Statistics, but also why they would want to. Spanning statistics basics like variables, constants, and sampling through to t-tests, multiple regression and factor analysis, it builds statistical literacy while also covering key research principles like research questions, error types and results reliability. It shows you how to: Describe data with graphs, tables, and numbers Calculate probability and value distributions Test a priori and post hoc hypotheses Conduct Chi-squared tests and observational studies Structure ANOVA, ANCOVA, and factorial designs Supported by lots of visuals and a website with interactive demonstrations, author video, and practice datasets, this book is the student-focused companion to support students through their statistics journeys.
Author : National Research Council,Division of Behavioral and Social Sciences and Education,Commission on Behavioral and Social Sciences and Education,Committee on National Statistics
Publisher : National Academies Press
Page : 233 pages
File Size : 40,8 Mb
Release : 1985-01-01
Category : Political Science
ISBN : 9780309034999
Author : D. A. De Vaus
Publisher : SAGE
Page : 436 pages
File Size : 51,8 Mb
Release : 2002-09-17
Category : Language Arts & Disciplines
ISBN : 0761959386
Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS
Author : National Research Council,Division of Behavioral and Social Sciences and Education,Commission on Behavioral and Social Sciences and Education,Committee on Basic Research in the Behavioral and Social Sciences
Publisher : National Academies Press
Page : 301 pages
File Size : 41,6 Mb
Release : 1988-02-01
Category : Science
ISBN : 9780309037495
This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.
Author : Shu-Heng Chen
Publisher : Springer
Page : 388 pages
File Size : 49,8 Mb
Release : 2018-11-21
Category : Computers
ISBN : 9783319954653
This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.
Author : Robert Ackland
Publisher : SAGE
Page : 224 pages
File Size : 51,7 Mb
Release : 2013-06-17
Category : Social Science
ISBN : 9781446283110
"Although written simply enough to be accessible to undergraduates, accomplished scholars are likely to appreciate it too. Reading it taught me quite a lot about a subject I thought I knew rather well." - Paul Vogt, Illinois State University "This book brings the art and science of building and applying innovative online research tools to students and faculty across the social sciences." - William H. Dutton, University of Oxford A comprehensive guide to the theory and practice of web Social Science. This book demonstrates how the web is being used to collect social research data, such as online surveys and interviews, as well as digital trace data from social media environments, such as Facebook and Twitter. It also illuminates how the advent of the web has led to traditional social science concepts and approaches being combined with those from other scientific disciplines, leading to new insights into social, political and economic behaviour. Situating social sciences in the digital age, this book aids: understanding of the fundamental changes to society, politics and the economy that have resulted from the advent of the web choice of appropriate data, tools and research methods for conducting research using web data learning how web data are providing new insights into long-standing social science research questions appreciation of how social science can facilitate an understanding of life in the digital age It is ideal for students and researchers across the social sciences, as well as those from information science, computer science and engineering who want to learn about how social scientists are thinking about and researching the web.
Author : Perry, S. Marshall
Publisher : IGI Global
Page : 328 pages
File Size : 44,6 Mb
Release : 2017-10-31
Category : Social Science
ISBN : 9781522536178
Making research in all fields of study readily available is imperative in order to circulate new information and upcoming trends. This is possible through the efficient utilization of collections of information. Maximizing Social Science Research Through Publicly Accessible Data Sets is an essential reference source for the latest academic perspectives on a wide range of methodologies and large data sets with the purpose of enhancing research in the areas of human society and social relationships. Featuring coverage on a broad range of topics such as student achievement, teacher efficacy, and instructional leadership, this book is ideally designed for academicians, researchers, and practitioners seeking material on the availability and distribution methods of research content.
Author : Kosuke Imai,Nora Webb Williams
Publisher : Princeton University Press
Page : 478 pages
File Size : 52,7 Mb
Release : 2022-08-02
Category : Social Science
ISBN : 9780691222288
A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior. Emphasizes hands-on learning, not paper-and-pencil statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
Author : G. David Garson
Publisher : Routledge
Page : 704 pages
File Size : 55,5 Mb
Release : 2021-11-30
Category : Psychology
ISBN : 9781000467086
Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.