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.
Exploring Data And Statistics In The Social Sciences
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Author : Tom Pering
language : en
Publisher: SAGE Publications Limited
Release Date : 2025-11-29
Exploring Data And Statistics In The Social Sciences written by Tom Pering and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-29 with Reference categories.
A succinct, no-frills introduction to social science data and statistics. It uses visual maps and prompts to communicate the potential of social data and to introduce the basic statistical tools available to beginners.
Applied Regression Models In The Social Sciences
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Author : Dudley L. Poston, Jr
language : en
Publisher: Cambridge University Press
Release Date : 2023-08-17
Applied Regression Models In The Social Sciences written by Dudley L. Poston, Jr 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.
This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.
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.
Introduction To Python Programming For Business And Social Science Applications
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Author : Frederick Kaefer
language : en
Publisher: SAGE Publications
Release Date : 2020-08-06
Introduction To Python Programming For Business And Social Science Applications written by Frederick Kaefer and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-06 with Business & Economics categories.
Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.
Handbook Of Computational Social Science Volume 1
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Author : Uwe Engel
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-10
Handbook Of Computational Social Science Volume 1 written by Uwe Engel and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.
The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field but also encourages growth in new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientifi c and engineering sectors.
Data Analysis For Social Science
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Author : Elena Llaudet
language : en
Publisher: Princeton University Press
Release Date : 2022-09-13
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 2022-09-13 with Social Science categories.
An ideal textbook for complete beginners—teaches from scratch R, statistics, and the fundamentals of quantitative social science Data Analysis for Social Science provides a friendly introduction to the statistical concepts and programming skills needed to conduct and evaluate social scientific studies. Assuming no prior knowledge of statistics and coding and only minimal knowledge of math, the book teaches the fundamentals of survey research, predictive models, and causal inference while analyzing data from published studies with the statistical program R. It teaches not only how to perform the data analyses but also how to interpret the results and identify the analyses’ strengths and limitations. Progresses by teaching how to solve one kind of problem after another, bringing in methods as needed. It teaches, in this order, how to (1) estimate causal effects with randomized experiments, (2) visualize and summarize data, (3) infer population characteristics, (4) predict outcomes, (5) estimate causal effects with observational data, and (6) generalize from sample to population. Flips the script of traditional statistics textbooks. It starts by estimating causal effects with randomized experiments and postpones any discussion of probability and statistical inference until the final chapters. This unconventional order engages students by demonstrating from the very beginning how data analysis can be used to answer interesting questions, while reserving more abstract, complex concepts for later chapters. Provides a step-by-step guide to analyzing real-world data using the powerful, open-source statistical program R, which is free for everyone to use. The datasets are provided on the book’s website so that readers can learn how to analyze data by following along with the exercises in the book on their own computer. Assumes no prior knowledge of statistics or coding. Specifically designed to accommodate students with a variety of math backgrounds. It includes supplemental materials for students with minimal knowledge of math and clearly identifies sections with more advanced material so that readers can skip them if they so choose. Provides cheatsheets of statistical concepts and R code. Comes with instructor materials (upon request), including sample syllabi, lecture slides, and additional replication-style exercises with solutions and with the real-world datasets analyzed. Looking for a more advanced introduction? Consider Quantitative Social Science by Kosuke Imai. In addition to covering the material in Data Analysis for Social Science, it teaches diffs-in-diffs models, heterogeneous effects, text analysis, and regression discontinuity designs, among other things.
Quantitative Social Science Data With R
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Author : Brian J. Fogarty
language : en
Publisher: SAGE
Release Date : 2023-03-11
Quantitative Social Science Data With R written by Brian J. Fogarty and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-11 with Reference categories.
This practical, step-by-step introduction to quantitative social science using R will provide low-level undergraduates with a foundation of understanding, ready to build upon as students advance throughout statistics
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.
Innovations And Technologies In Science Stem Education Opportunities Challenges And Sustainable Practices
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Author : Wang-Kin Chiu
language : en
Publisher: Frontiers Media SA
Release Date : 2024-04-01
Innovations And Technologies In Science Stem Education Opportunities Challenges And Sustainable Practices written by Wang-Kin Chiu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-01 with Education categories.
In our digital era, harnessing innovations and emerging technologies to support teaching and learning has been an important research area in the field of education around the world. In science/STEM education, technologies can be leveraged to present and visualize scientific theories and concepts effectively, while the development of pedagogic innovations usually requires collective, inter-disciplinary research efforts. In addition, emerging technologies can better support teachers to assess students’ learning performance in STEM subjects and offer students viable virtual environments to facilitate laboratory-based learning, thereby contributing to sustainable development in both K-12 and higher education.