Data Analysis For The Social Sciences
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Data Analysis For Social Science
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Author : Elena Llaudet
language : en
Publisher: Princeton University Press
Release Date : 2022-11-29
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 2022-11-29 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"--
Theory Based Data Analysis For The Social Sciences
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Author : Carol S. Aneshensel
language : en
Publisher: SAGE
Release Date : 2013
Theory Based Data Analysis For The Social Sciences written by Carol S. Aneshensel and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Social Science categories.
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Data Analysis For Social Science
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Author : Elena Llaudet
language : en
Publisher: Princeton University Press
Release Date : 2022-11-29
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 2022-11-29 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"--
Data Analytics For The Social Sciences
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Author : G. David Garson
language : en
Publisher: Routledge
Release Date : 2021-11-30
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 2021-11-30 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.
Data Analysis For The Social Sciences
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Author : Douglas Bors
language : en
Publisher: SAGE
Release Date : 2018-01-08
Data Analysis For The Social Sciences written by Douglas Bors and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-08 with Reference categories.
Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows students not only how to apply newfound knowledge using IBM SPSS Statistics, but also why they would want to - all supported by lots of visuals, interactive demonstrations, author videos, and practice datasets.
Statistics And Data Analysis For Social Science
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Author : Eric J. Krieg
language : en
Publisher: SAGE Publications
Release Date : 2019-07-11
Statistics And Data Analysis For Social Science written by Eric J. Krieg and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Social Science categories.
Apply statistics to your everyday life. Statistics and Data Analysis for Social Science helps students to build a strong foundational understanding of statistics by providing clarity around when and why statistics useful. Rather than focusing on the "how to" of statistics, author Eric J. Krieg simplifies the complexity of statistical calculations by introducing only what is necessary to understanding each concept. Every chapter is written around and applied to a different social problem or issues—enabling students to broaden their imagination about the statistical "tools" that can be used to make sense of our world and, maybe, to make the world a better place. In addition to updating all the tables and examples with new data, the Second Edition has replaced the section on SPSS with three new sets of exercises at the end of each chapter: Chapter Exercises for students complete during their reading and bring questions to class, In-Class Exercises that focus on the areas that students struggled with during their reading, and Homework Exercises that can be assigned if students need extra practice with the concepts.
Text Mining For Qualitative Data Analysis In The Social Sciences
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Author : Gregor Wiedemann
language : en
Publisher: Springer
Release Date : 2016-08-23
Text Mining For Qualitative Data Analysis In The Social Sciences written by Gregor Wiedemann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-23 with Social Science categories.
Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of “democratic demarcation” in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.
Using R For Data Analysis In Social Sciences
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Author : Quan Li
language : en
Publisher: Oxford University Press
Release Date : 2018
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 with Business & Economics 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.
Theory Based Data Analysis For The Social Sciences
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Author :
language : en
Publisher:
Release Date : 2013
Theory Based Data Analysis For The Social Sciences written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Social sciences categories.
"This book presents the elaboration model for the multivariate analysis of observational quantitative data using two complimentary strategies: an exclusionary strategy and an inclusive strategy. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions."--Page 4 of cover.
Research Methodology And Data Analysis In Humanities Social Sciences
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Author : Rajesh Ekka
language : en
Publisher: Lulu.com
Release Date :
Research Methodology And Data Analysis In Humanities Social Sciences written by Rajesh Ekka and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.