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Introduction To R For Social Scientists

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Introduction To R For Social Scientists

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Author : Ryan Kennedy
language : en
Publisher: CRC Press
Release Date : 2021-02-11

Introduction To R For Social Scientists written by Ryan Kennedy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-11 with Mathematics categories.

Introduction to R for Social Scientists: A Tidy Programming Approach introduces the Tidy approach to programming in R for social science research to help quantitative researchers develop a modern technical toolbox. The Tidy approach is built around consistent syntax, common grammar, and stacked code, which contribute to clear, efficient programming. The authors include hundreds of lines of code to demonstrate a suite of techniques for developing and debugging an efficient social science research workflow. To deepen the dedication to teaching Tidy best practices for conducting social science research in R, the authors include numerous examples using real world data including the American National Election Study and the World Indicators Data. While no prior experience in R is assumed, readers are expected to be acquainted with common social science research designs and terminology. Whether used as a reference manual or read from cover to cover, readers will be equipped with a deeper understanding of R and the Tidyverse, as well as a framework for how best to leverage these powerful tools to write tidy, efficient code for solving problems. To this end, the authors provide many suggestions for additional readings and tools to build on the concepts covered. They use all covered techniques in their own work as scholars and practitioners.

Introduction To R For Social Scientists

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Author : Ryan Kennedy
language : en
Publisher: CRC Press
Release Date : 2021-03-08

A Guide To R For Social And Behavioral Science Statistics

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Author : Brian Joseph Gillespie
language : en
Publisher: SAGE Publications
Release Date : 2020-02-07

A Guide To R For Social And Behavioral Science Statistics written by Brian Joseph Gillespie and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-07 with Social Science categories.

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate students, shown in the R statistical language using RStudio®. The book is geared toward social and behavioral science statistics students, especially those with no background in computer science. Written as a companion book to be used alongside a larger introductory statistics text, the text follows the most common progression of statistics for social scientists. The guide also serves as a companion for conducting data analysis in a research methods course or as a stand-alone R and statistics text. This guide can teach anyone how to use R to analyze data, and uses frequent reminders of basic statistical concepts to accompany instructions in R to help walk students through the basics of learning how to use R for statistics.

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.

The Limits Of Social Science

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Author : Martyn Hammersley
language : en
Publisher: SAGE
Release Date : 2014-06-16

The Limits Of Social Science written by Martyn Hammersley and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-16 with Social Science categories.

What forms of knowledge can social science claim to produce? Does it employ causal analysis, and if so what does this entail? What role should values play in the work of social scientists? These are the questions addressed in this book. They are closely interrelated, and the answers offered here challenge many currently prevailing assumptions. They carry implications both for research practice, quantitative or qualitative, and for the public claims that social scientists make about the value of their work. The arguments underpinning this challenge to conventional wisdom are laid out in detail in the first half of the book. In later chapters their implications are explored for two substantive areas of intrinsic importance: the study of social mobility and educational inequalities; and explanations for urban riots, notably those that took place in London and other English cities in the summer of 2011.

Quantitative Social Science Data With R

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Author : Brian J. Fogarty
language : en
Publisher: SAGE
Release Date : 2018-11-24

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 2018-11-24 with Reference categories.

Relevant, engaging, and packed with student-focused learning features, this book provides the basic step-by-step introduction to quantitative research and data every student needs.

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.

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.

Applying The Rasch Model In Social Sciences Using R

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Author : Iasonas Lamprianou
language : en
Publisher: Routledge
Release Date : 2019-12-12

Applying The Rasch Model In Social Sciences Using R written by Iasonas Lamprianou and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-12 with Psychology categories.

This unique text provides a step-by-step beginner’s guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable ("latent") variables. Each chapter is devoted to one popular Rasch model, ranging from the least to the most complex. Through a freely available and user-friendly package, BlueSky Statistics, Lamprianou offers a range of options for presenting results, critically examines the strengths and weaknesses of applying the Rasch model in each instance, and suggests more effective methodologies where applicable. With a focus on simple software code which does not assume extensive mathematical knowledge, the reader is initially introduced to the so-called simple Rasch Model to construct a "political activism" variable out of a group of dichotomously scored questions. In subsequent chapters, the book covers everything from the Rating Scale to the Many-facets Rasch model. The final chapter even showcases a complete mock manuscript, demonstrating how a Rasch-based paper on the identification of online hate speech should look like. Combining theoretical rigor and real-world examples with empirical datasets from published papers, this book is essential reading for students and researchers alike who aspire to use Rasch models in their research.

Computational Social Science

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Author : R. Michael Alvarez
language : en
Publisher: Cambridge University Press
Release Date : 2016-03-10

Computational Social Science written by R. Michael Alvarez 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 2016-03-10 with Political Science categories.

This book provides an overview of cutting-edge approaches to computational social science.

Introduction To R For Social Scientists

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