Sharing Social Science Data
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| Author | : Joan E. Sieber |
| Publisher | : SAGE |
| Total Pages | : 177 |
| Release | : 1991-02-12 |
| Genre | : Education |
| ISBN | : 0803940831 |
This book represents the major accomplishments of social scientists who have pioneered in data sharing, highlighting the advantages for social science. It includes an examination of the reasons for data sharing, the specific sharing practices in various disciplines, the factors affecting the usefulness of shared data and individual and institutional concerns about data sharing. It will be useful to academics across the social sciences.
| Author | : Elena Llaudet |
| Publisher | : Princeton University Press |
| Total Pages | : 256 |
| Release | : 2022-11-29 |
| Genre | : Computers |
| ISBN | : 0691199434 |
"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 | : Phillip D. Brooker |
| Publisher | : SAGE |
| Total Pages | : 370 |
| Release | : 2019-12-09 |
| Genre | : Social Science |
| ISBN | : 1526486342 |
As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including: the fundamentals of why and how to do your own programming in social scientific research, questions of ethics and research design, a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more. Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.
| Author | : Anol Bhattacherjee |
| Publisher | : CreateSpace |
| Total Pages | : 156 |
| Release | : 2012-04-01 |
| Genre | : Science |
| ISBN | : 9781475146127 |
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 | : Steve W. Witt |
| Publisher | : Walter de Gruyter |
| Total Pages | : 138 |
| Release | : 2010-06-29 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 3110232154 |
This volume focuses on practical and empirical accounts of organizational change in the social sciences and impacts upon the professional skills, collections, and services within social science libraries. Section one focuses upon the question of interdisciplinary within social science libraries and the role of libraries to both react to and facilitate paradigm shifts in research and science. Section two focuses on the rise of data as a resource to be collected and shared within social science libraries. The third section focuses on the role of librarians to facilitate the development of social organizations that develop around new technologies and research communities. Changed role of librarians within social science libraries Describes new developments of social organizations Essential for librarians
| Author | : Garret Christensen |
| Publisher | : University of California Press |
| Total Pages | : 266 |
| Release | : 2019-07-23 |
| Genre | : Social Science |
| ISBN | : 0520296958 |
Recently, social science has had numerous episodes of influential research that was found invalid when placed under rigorous scrutiny. The growing sense that many published results are potentially erroneous has made those conducting social science research more determined to ensure the underlying research is sound. Transparent and Reproducible Social Science Research is the first book to summarize and synthesize new approaches to combat false positives and non-reproducible findings in social science research, document the underlying problems in research practices, and teach a new generation of students and scholars how to overcome them. Understanding that social science research has real consequences for individuals when used by professionals in public policy, health, law enforcement, and other fields, the book crystallizes new insights, practices, and methods that help ensure greater research transparency, openness, and reproducibility. Readers are guided through well-known problems and are encouraged to work through new solutions and practices to improve the openness of their research. Created with both experienced and novice researchers in mind, Transparent and Reproducible Social Science Research serves as an indispensable resource for the production of high quality social science research.
| Author | : Kosuke Imai |
| Publisher | : Princeton University Press |
| Total Pages | : 464 |
| Release | : 2021-03-16 |
| Genre | : Political Science |
| ISBN | : 0691191093 |
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
| Author | : Ian Foster |
| Publisher | : CRC Press |
| Total Pages | : 493 |
| Release | : 2016-08-10 |
| Genre | : Mathematics |
| ISBN | : 1498751431 |
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
| Author | : Jose Manuel Magallanes Reyes |
| Publisher | : Cambridge University Press |
| Total Pages | : 317 |
| Release | : 2017-09-21 |
| Genre | : Computers |
| ISBN | : 1107117410 |
This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
| Author | : Gyamfi, Albert |
| Publisher | : IGI Global |
| Total Pages | : 275 |
| Release | : 2021-06-18 |
| Genre | : Business & Economics |
| ISBN | : 1799867943 |
Knowledge management has always been about the process of creating, sharing, using, and applying knowledge within and between organizations. Before the advent of information systems, knowledge management processes were manual or offline. However, the emergence and eventual evolution of information systems created the possibility for the gradual but slow automation of knowledge management processes. These digital technologies enable data capture, data storage, data mining, data analytics, and data visualization. The value provided by such technologies is enhanced and distributed to organizations as well as customers using the digital technologies that enable interconnectivity. Today, the fine line between the technologies enabling the technology-driven external pressures and data-driven internal organizational pressures is blurred. Therefore, how technologies are combined to facilitate knowledge management processes is becoming less standardized. This results in the question of how the current advancement in digital technologies affects knowledge management processes both within and outside organizations. Digital Technology Advancements in Knowledge Management addresses how various new and emerging digital technologies can support knowledge management processes within organizations or outside organizations. Case studies and practical tips based on research on the emerging possibilities for knowledge management using these technologies is discussed within the chapters of this book. It both builds on the available literature in the field of knowledge management while providing for further research opportunities in this dynamic field. This book highlights topics such as human-robot interaction, big data analytics, software development, keyword extraction, and artificial intelligence and is ideal for technology developers, academics, researchers, managers, practitioners, stakeholders, and students who are interested in the adoption and implementation of new digital technologies for knowledge creation, sharing, aggregation, and storage.
