Data Management For Social Scientists
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Data Management For Social Scientists
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Author : Nils B. Weidmann
language : en
Publisher: Cambridge University Press
Release Date : 2023-03-09
Data Management For Social Scientists written by Nils B. Weidmann and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-09 with Social Science categories.
Equips social scientists with the tools and techniques to conduct quantitative research in the age of big data.
Data Management In R
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Author : Martin Elff
language : en
Publisher: SAGE
Release Date : 2020-12-02
Data Management In R written by Martin Elff and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Reference categories.
An invaluable step-by-step, pedagogically engaging guide to data management in R for social science researchers. This book shows students how to recode and document data, as well as how to combine data from different sources, or import from statistical packages other than R.
An Introduction To Data Management In The Behavioral And Social Sciences
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Author : Sheldon Blackman
language : en
Publisher: John Wiley & Sons
Release Date : 1971
An Introduction To Data Management In The Behavioral And Social Sciences written by Sheldon Blackman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Sciences sociales - Informatique categories.
Principles Of Data Management And Presentation
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Author : Dr. John P. Hoffmann
language : en
Publisher: Univ of California Press
Release Date : 2017-07-03
Principles Of Data Management And Presentation written by Dr. John P. Hoffmann and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-03 with Social Science categories.
The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences. Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including: • how to narrow a research topic to a specific research question • how to access and organize data that are useful for answering a research question • how to use software such as Stata, SPSS, and SAS to manage data • how to present data so that they convey a clear and effective message A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab.
Research Data Management
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Author : Joyce M. Ray
language : en
Publisher: Purdue University Press
Release Date : 2014
Research Data Management written by Joyce M. Ray and has been published by Purdue University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Business & Economics categories.
It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations.
Big Data In Computational Social Science And Humanities
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Author : Shu-Heng Chen
language : en
Publisher: Springer
Release Date : 2018-11-21
Big Data In Computational Social Science And Humanities written by Shu-Heng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-21 with Computers categories.
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.
Managing And Sharing Research Data
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Author : Louise Corti
language : en
Publisher: SAGE
Release Date : 2019-10-07
Managing And Sharing Research Data written by Louise Corti and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-07 with Business & Economics categories.
Written by experts at the UK Data Archive, with over thirty years of experience in working with and teaching people to work with data, this book is the globally-reaching guide for any postgraduate student or researcher looking to build their data management skills. Focused on both primary and secondary data and packed with checklists and templates, it contains everything readers need to know for managing all types data before, during, and after the research process. Building on foundational data management techniques, it offers practical advice and insight into the unique skills needed to work with newer forms of data, like social media and big data. It also demonstrates how to: - Identify quality data that is credible, ethically-sound, and available for use - Choose and collect data suitable for particular research questions and project scopes - Work with personal, communal, administrative, and other sensitive and public data - Make the most of metadata - Visualise and share data using innovative platforms like blogs, infographics, and podcasts.
Introduction To Data Science For Social And Policy Research
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Author : Jose Manuel Magallanes Reyes
language : en
Publisher: Cambridge University Press
Release Date : 2017-09-21
Introduction To Data Science For Social And Policy Research written by Jose Manuel Magallanes Reyes and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-21 with Mathematics categories.
This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
Preparing Data For Sharing
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Author :
language : en
Publisher: Amsterdam University Press
Release Date : 2010
Preparing Data For Sharing written by and has been published by Amsterdam University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Social Science categories.
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.
Applications Of Data Management And Analysis
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Author : Mohammad Moshirpour
language : en
Publisher: Springer
Release Date : 2018-10-04
Applications Of Data Management And Analysis written by Mohammad Moshirpour and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-04 with Business & Economics categories.
This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry. The chapters cover effective approaches in dealing with the inherent complexity and increasing demands of big data management from an applications perspective. Various case studies included have been reported by data analysis experts who work closely with their clients in such fields as education, banking, and telecommunications. Understanding how data management has been adapted to these applications will help students, instructors and professionals in the field. Application areas also include the fields of social network analysis, bioinformatics, and the oil and gas industries.