Using R For Data Analysis In Social Sciences
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Using R For Data Analysis In Social Sciences
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Author : Quan Li
language : en
Publisher: Oxford University Press
Release Date : 2018-05-09
Using R For Data Analysis In Social Sciences written by Quan Li and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-09 with Political Science categories.
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.
Data Analysis For Social Science
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Author : Elena Llaudet
language : en
Publisher: Princeton University Press
Release Date : 2023
Data Analysis For Social Science written by Elena Llaudet and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Computers categories.
"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"--
Advances In Social Science Research Using R
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Author : Hrishikesh D. Vinod
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-24
Advances In Social Science Research Using R written by Hrishikesh D. Vinod and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-24 with Business & Economics categories.
Quantitative social science research has been expanding due to the ava- ability of computers and data over the past few decades. Yet the textbooks and supplements for researchers do not adequately highlight the revolution created by the R software [2] and graphics system. R is fast becoming the l- gua franca of quantitative research with some 2000 free specialized packages, where the latest versions can be downloaded in seconds. Many packages such as “car” [1] developed by social scientists are popular among all scientists. An early 2009 article [3] in the New York Times notes that statisticians, engineers and scientists without computer programming skills ?nd R “easy to use.” A common language R can readily promote deeper mutual respect and understanding of unique problems facing quantitative work in various social sciences. Often the solutions developed in one ?eld can be extended and used in many ?elds. This book promotes just such exchange of ideas across many social sciences. Since Springer has played a leadership role in promoting R, we are fortunate to have Springer publish this book. A Conference on Quantitative Social Science Research Using R was held in New York City at the Lincoln Center campus of Fordham University, June 18–19, 2009. This book contains selected papers presented at the conference, representing the “Proceedings” of the conference.
Applied Regression Models In The Social Sciences
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Author : Dudley L. Poston
language : en
Publisher: Cambridge University Press
Release Date : 2023-08-17
Applied Regression Models In The Social Sciences written by Dudley L. Poston 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 2023-08-17 with Social Science categories.
An accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.
Data Analytics For The Social Sciences
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Author : G. David Garson
language : en
Publisher: Routledge
Release Date : 2021-11-29
Data Analytics For The Social Sciences written by G. David Garson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.
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.
Visualization For Social Data Science
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Author : Roger Beecham
language : en
Publisher: CRC Press
Release Date : 2025-09-05
Visualization For Social Data Science written by Roger Beecham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-05 with Mathematics categories.
"This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't wait to use this book in my classes."- Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York "A book that gives learners the inspiration, knowledge and worked examples to create cutting edge visualisations of their own."- James Chesire, Professor of Geographic Information and Cartography, University College London Visualization for Social Data Science provides end-to-end skills in visual data analysis. The book demonstrates how data graphics and modern statistics can be used in tandem to process, explore, model and communicate data-driven social science. It is packed with detailed data analysis examples, pushing you to do visual data analysis. As well as introducing, and demonstrating with code, a wide range of data visualizations for exploring patterns in data, Visualization for Social Data Science shows how models can be integrated with graphics to emphasise important structure and de-emphasise spurious structure and the role of data graphics in scientific communication -- in building trust and integrity. Many of the book’s influences are from data journalism, as well as information visualization and cartography. Each chapter introduces statistical and graphical ideas for analysis, underpinned by real social science datasets. Those ideas are then implemented via principled, step-by-step, workflows in the programming environment R. Key features include: • Extensive real-world data sets and data analysis scenarios in Geography, Public Health, Transportation, Political Science; • Code examples fully-integrated into main text, with code that builds in complexity and sophistication; • Quarto template files for each chapter to support literate programming practices; • Functional programming examples, using tidyverse, for generating empirical statistics (bootstrap resamples, permutation tests) and working programmatically over model outputs; • Unusual but important programming tricks for generating sophisticated data graphics such as network visualizations, dot-density maps, OD maps, glyphmaps, icon arrays, hypothetical outcome plots and graphical line-ups plots. Every data graphic in the book is implemented via ggplot2. • Chapters on uncertainty visualization and data storytelling that are uniquely accompanied with detailed, worked examples.
Theoretical And Methodological Approaches To Social Sciences And Knowledge Management
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Author : Asunción Lopez-Varela Azcárate
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-08-16
Theoretical And Methodological Approaches To Social Sciences And Knowledge Management written by Asunción Lopez-Varela Azcárate and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-16 with Business & Economics categories.
This is a unique and groundbreaking collection of questions and answers coming from higher education institutions on diverse fields and across a wide spectrum of countries and cultures. It creates routes for further innovation, collaboration amidst the Sciences (both Natural and Social), the Humanities, and the private and public sectors of society. The chapters speak across sociocultural concerns, education, welfare and artistic sectors under the common desire for direct responses in more effective ways by means of interaction across societal structures.
Data Science
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Author : Prabhu TL
language : en
Publisher: NestFame Creations Pvt Ltd.
Release Date : 2025-04-12
Data Science written by Prabhu TL and has been published by NestFame Creations Pvt Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-12 with Computers categories.
Data Science: From Basics to Advanced Unlock the Power of Data to Build Intelligent Solutions and Transform Your Career Are you ready to master one of the most in-demand and future-proof skills of the 21st century? Whether you're a beginner, student, working professional, or tech enthusiast—this comprehensive guide is your ultimate roadmap to becoming a data science expert. “Data Science: From Basics to Advanced” takes you on a complete journey through the world of data, starting from foundational concepts and evolving all the way to advanced machine learning, deep learning, and real-world deployment. ✅ What You’ll Learn Inside: 📊 Statistics, Probability & Linear Algebra — The math behind the magic 🐍 Python Programming — Clean and efficient data handling with NumPy and pandas 🔍 Exploratory Data Analysis — Visualize, understand, and tell stories with data 🤖 Machine Learning & Deep Learning — Build, train, and tune powerful models 🧠 Natural Language Processing, Time Series, and Computer Vision ☁️ Cloud Tools, Big Data, and MLOps — Deploy scalable solutions using AWS, GCP, and more 🔐 Bias, Fairness & Data Ethics — Build responsible, human-centered AI 🧳 Career Tools — Portfolio templates, interview prep, certifications, and roadmaps 💡 Who This Book Is For: Beginners looking for a step-by-step introduction to data science Professionals seeking to upskill or transition into AI/ML roles Students preparing for internships and job interviews Entrepreneurs and business leaders leveraging data-driven strategies 🎓 Includes: ✅ Real-world projects and use cases ✅ Sample code and reusable templates ✅ Cheat sheets, glossary, and portfolio guidance ✅ Companion resources and learning roadmap If you've ever wanted to extract insight from raw data, build machine learning models, or launch a data science career, this is the book you've been waiting for. 🔥 Your journey into data starts now. 📘 Get your copy of Data Science: From Basics to Advanced and turn information into impact.
Handbook Of Research Methods And Applications In Spatially Integrated Social Science
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Author : Robert Stimson
language : en
Publisher: Edward Elgar Publishing
Release Date : 2014-07-31
Handbook Of Research Methods And Applications In Spatially Integrated Social Science written by Robert Stimson and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-31 with Social Science categories.
The chapters in this book provide coverage of the theoretical underpinnings and methodologies that typify research using a Spatially Integrated Social Science (SISS) approach. This insightful Handbook is intended chiefly as a primer for students and bu
Handbook Of Spatial Analysis In The Social Sciences
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Author : Sergio J. Rey
language : en
Publisher: Edward Elgar Publishing
Release Date : 2022-11-18
Handbook Of Spatial Analysis In The Social Sciences written by Sergio J. Rey and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-18 with Technology & Engineering categories.
Providing an authoritative assessment of the current landscape of spatial analysis in the social sciences, this cutting-edge Handbook covers the full range of standard and emerging methods across the social science domain areas in which these methods are typically applied. Accessible and comprehensive, it expertly answers the key questions regarding the dynamic intersection of spatial analysis and the social sciences.