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| Author | : Elena Llaudet |
| Publisher | : Princeton University Press |
| Total Pages | : 256 |
| Release | : 2022-11-29 |
| Genre | : Computers |
| ISBN | : 0691199434 |
Download Data Analysis for Social Science Book in PDF, ePub and Kindle
"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 | : Ian Foster |
| Publisher | : CRC Press |
| Total Pages | : 413 |
| Release | : 2020-11-17 |
| Genre | : Mathematics |
| ISBN | : 1000208591 |
Download Big Data and Social Science Book in PDF, ePub and Kindle
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
| Author | : Ian Foster |
| Publisher | : CRC Press |
| Total Pages | : 493 |
| Release | : 2016-08-10 |
| Genre | : Mathematics |
| ISBN | : 1498751431 |
Download Big Data and Social Science Book in PDF, ePub and Kindle
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 | : G. David Garson |
| Publisher | : Routledge |
| Total Pages | : 704 |
| Release | : 2021-11-30 |
| Genre | : Psychology |
| ISBN | : 1000467082 |
Download Data Analytics for the Social Sciences Book in PDF, ePub and Kindle
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.
| Author | : Kosuke Imai |
| Publisher | : Princeton University Press |
| Total Pages | : 464 |
| Release | : 2021-03-16 |
| Genre | : Political Science |
| ISBN | : 0691191093 |
Download Quantitative Social Science Book in PDF, ePub and Kindle
"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 | : N. Carlo Lauro |
| Publisher | : Springer |
| Total Pages | : 300 |
| Release | : 2017-11-17 |
| Genre | : Social Science |
| ISBN | : 3319554778 |
Download Data Science and Social Research Book in PDF, ePub and Kindle
This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.
| Author | : Bernie Hogan |
| Publisher | : SAGE |
| Total Pages | : 334 |
| Release | : 2022-11-23 |
| Genre | : Social Science |
| ISBN | : 1529737176 |
Download From Social Science to Data Science Book in PDF, ePub and Kindle
From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding of computational techniques and seeing the bigger picture. With key features such as tables, figures, step-by-step instruction and explanations giving a wider context, Hogan presents a clear and concise analysis of key data collection and skills in Python.
| Author | : Mark Andrews |
| Publisher | : SAGE |
| Total Pages | : 576 |
| Release | : 2021-03-31 |
| Genre | : Social Science |
| ISBN | : 1529752698 |
Download Doing Data Science in R Book in PDF, ePub and Kindle
This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis. Introducing the fundamentals of data science and R before moving into more advanced topics like Multilevel Models and Probabilistic Modelling with Stan, it builds knowledge and skills gradually. This book: Focuses on providing practical guidance for all aspects, helping readers get to grips with the tools, software, and statistical methods needed to provide the right type and level of analysis their data requires Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social science skills Introduces R at the outset and includes extensive worked examples and R code every step of the way, ensuring students see the value of R and its connection to methods while providing hands-on practice in the software Provides examples and datasets from different disciplines and locations demonstrate the widespread relevance, possible applications, and impact of data science across the social sciences.
| Author | : Jose Manuel Magallanes Reyes |
| Publisher | : Cambridge University Press |
| Total Pages | : 317 |
| Release | : 2017-09-21 |
| Genre | : Mathematics |
| ISBN | : 1107117410 |
Download Introduction to Data Science for Social and Policy Research Book in PDF, ePub and Kindle
This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
| Author | : Massimo Lapucci |
| Publisher | : Springer Nature |
| Total Pages | : 107 |
| Release | : 2021-10-13 |
| Genre | : Science |
| ISBN | : 3030789853 |
Download Data Science for Social Good Book in PDF, ePub and Kindle
This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact – identifying a social need, targeting an intervention, measuring impact – and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.
