Data Analysis For Social Science

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Data Analysis for Social Science

Elena Llaudet,Kosuke Imai
Data Analysis for Social Science Book PDF

Author : Elena Llaudet,Kosuke Imai
Publisher : Princeton University Press
Page : 256 pages
File Size : 46,6 Mb
Release : 2022-11-29
Category : Computers
ISBN : 9780691199436

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Data Analysis for Social Science by Elena Llaudet,Kosuke Imai Pdf

"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 Analysis for Social Science

Elena Llaudet,Kosuke Imai
Data Analysis for Social Science Book PDF

Author : Elena Llaudet,Kosuke Imai
Publisher : Princeton University Press
Page : 257 pages
File Size : 42,5 Mb
Release : 2022-09-13
Category : Social Science
ISBN : 9780691229348

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Data Analysis for Social Science by Elena Llaudet,Kosuke Imai Pdf

An ideal textbook for an introductory course on quantitative methods for social scientists—assumes no prior knowledge of statistics or coding Data Analysis for Social Science provides a friendly introduction to the statistical concepts and programming skills needed to conduct and evaluate social scientific studies. Using plain language and assuming no prior knowledge of statistics and coding, the book provides a step-by-step guide to analyzing real-world data with the statistical program R for the purpose of answering a wide range of substantive social science questions. It teaches not only how to perform the analyses but also how to interpret results and identify strengths and limitations. This one-of-a-kind textbook includes supplemental materials to accommodate students with minimal knowledge of math and clearly identifies sections with more advanced material so that readers can skip them if they so choose. Analyzes real-world data using the powerful, open-sourced statistical program R, which is free for everyone to use Teaches how to measure, predict, and explain quantities of interest based on data Shows how to infer population characteristics using survey research, predict outcomes using linear models, and estimate causal effects with and without randomized experiments Assumes no prior knowledge of statistics or coding Specifically designed to accommodate students with a variety of math backgrounds Provides cheatsheets of statistical concepts and R code Supporting materials available online, including real-world datasets and the code to analyze them, plus—for instructor use—sample syllabi, sample lecture slides, additional datasets, and additional exercises with solutions 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.

Data Analytics for the Social Sciences

G. David Garson
Data Analytics for the Social Sciences Book PDF

Author : G. David Garson
Publisher : Routledge
Page : 704 pages
File Size : 44,6 Mb
Release : 2021-11-30
Category : Psychology
ISBN : 9781000467086

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Data Analytics for the Social Sciences by G. David Garson Pdf

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.

Statistics and Data Analysis for Social Science

Eric J. Krieg
Statistics and Data Analysis for Social Science Book PDF

Author : Eric J. Krieg
Publisher : SAGE Publications
Page : 367 pages
File Size : 55,5 Mb
Release : 2019-07-11
Category : Social Science
ISBN : 9781544352695

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Statistics and Data Analysis for Social Science by Eric J. Krieg Pdf

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.

Quantitative Social Science

Kosuke Imai,Lori D. Bougher
Quantitative Social Science Book PDF

Author : Kosuke Imai,Lori D. Bougher
Publisher : Princeton University Press
Page : 464 pages
File Size : 49,6 Mb
Release : 2021-03-16
Category : Political Science
ISBN : 9780691191096

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Quantitative Social Science by Kosuke Imai,Lori D. Bougher Pdf

"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"--

Data Analysis for the Social Sciences

Douglas Bors
Data Analysis for the Social Sciences Book PDF

Author : Douglas Bors
Publisher : SAGE
Page : 1115 pages
File Size : 40,8 Mb
Release : 2018-01-08
Category : Social Science
ISBN : 9781526422309

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Data Analysis for the Social Sciences by Douglas Bors Pdf

′This book fosters in-depth understanding of the logic underpinning the most common statistical tests within the behavioural sciences. By emphasising the shared ground between these tests, the author provides crucial scaffolding for students as they embark upon their research journey.′ —Ruth Horry, Psychology, Swansea University ′This unique text presents the conceptual underpinnings of statistics as well as the computation and application of statistics to real-life situations--a combination rarely covered in one book. A must-have for students learning statistical techniques and a go-to handbook for experienced researchers.′ —Barbra Teater, Social Work, College of Staten Island, City University of New York Accessible, engaging, and informative, this book will help any social science student approach statistics with confidence. With a well-paced and well-judged integrated approach rather than a simple linear trajectory, this book progresses at a realistic speed that matches the pace at which statistics novices actually learn. 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. Spanning statistics basics like variables, constants, and sampling through to t-tests, multiple regression and factor analysis, it builds statistical literacy while also covering key research principles like research questions, error types and results reliability. It shows you how to: Describe data with graphs, tables, and numbers Calculate probability and value distributions Test a priori and post hoc hypotheses Conduct Chi-squared tests and observational studies Structure ANOVA, ANCOVA, and factorial designs Supported by lots of visuals and a website with interactive demonstrations, author video, and practice datasets, this book is the student-focused companion to support students through their statistics journeys.

Analyzing Social Science Data

D. A. De Vaus
Analyzing Social Science Data Book PDF

Author : D. A. De Vaus
Publisher : SAGE
Page : 436 pages
File Size : 42,5 Mb
Release : 2002-09-17
Category : Language Arts & Disciplines
ISBN : 0761959386

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Analyzing Social Science Data by D. A. De Vaus Pdf

Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS

Data Analysis for Social Science

Elena Llaudet,Kosuke Imai
Data Analysis for Social Science Book PDF

Author : Elena Llaudet,Kosuke Imai
Publisher : Princeton University Press
Page : 256 pages
File Size : 50,5 Mb
Release : 2022-11-29
Category : Computers
ISBN : 9780691199436

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Data Analysis for Social Science by Elena Llaudet,Kosuke Imai Pdf

"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

Carol S. Aneshensel
Theory Based Data Analysis for the Social Sciences Book PDF

Author : Carol S. Aneshensel
Publisher : SAGE
Page : 473 pages
File Size : 47,5 Mb
Release : 2013
Category : Social Science
ISBN : 9781412994354

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Theory-Based Data Analysis for the Social Sciences by Carol S. Aneshensel Pdf

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.

Text Mining for Qualitative Data Analysis in the Social Sciences

Gregor Wiedemann
Text Mining for Qualitative Data Analysis in the Social Sciences Book PDF

Author : Gregor Wiedemann
Publisher : Springer
Page : 294 pages
File Size : 53,8 Mb
Release : 2016-08-23
Category : Social Science
ISBN : 9783658153090

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Text Mining for Qualitative Data Analysis in the Social Sciences by Gregor Wiedemann Pdf

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

Quan Li
Using R for Data Analysis in Social Sciences Book PDF

Author : Quan Li
Publisher : Oxford University Press
Page : 369 pages
File Size : 50,8 Mb
Release : 2018
Category : Business & Economics
ISBN : 9780190656218

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Using R for Data Analysis in Social Sciences by Quan Li Pdf

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.

Statistics and Data Analysis for Social Science

Eric J. Krieg
Statistics and Data Analysis for Social Science Book PDF

Author : Eric J. Krieg
Publisher : Pearson
Page : 392 pages
File Size : 50,6 Mb
Release : 2013-11-01
Category : Social sciences
ISBN : 1292041234

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Statistics and Data Analysis for Social Science by Eric J. Krieg Pdf

For a one-semester, undergraduate introductory course in social statistics. Statistical tools for understanding the social world. This first edition text seeks to answer the question, universally asked by the social science student, Why statistics? The author introduces only those statistical concepts that are necessary to understand, interpret, and present social science research. All concepts are introduced in the context of a social science application, and strong emphasis is placed on demonstrating what data looks like, as opposed to giving theoretical explanations. Complexity of calculations is reduced to those elements necessary for understanding the statistical concept. Optional technology use is paired with the core elements of the course, making this text a pragmatic and engaging introduction to the practice of social statistics.

Data Science and Social Research

N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
Data Science and Social Research Book PDF

Author : N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
Publisher : Springer
Page : 300 pages
File Size : 40,7 Mb
Release : 2017-11-17
Category : Social Science
ISBN : 9783319554778

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Data Science and Social Research by N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino Pdf

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.

Qualitative Data Analysis

Ian Dey
Qualitative Data Analysis Book PDF

Author : Ian Dey
Publisher : Routledge
Page : 309 pages
File Size : 46,7 Mb
Release : 2003-09-02
Category : Psychology
ISBN : 9781134931460

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Qualitative Data Analysis by Ian Dey Pdf

Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.

Applied Panel Data Analysis for Economic and Social Surveys

Hans-Jürgen Andreß,Katrin Golsch,Alexander W. Schmidt
Applied Panel Data Analysis for Economic and Social Surveys Book PDF

Author : Hans-Jürgen Andreß,Katrin Golsch,Alexander W. Schmidt
Publisher : Springer Science & Business Media
Page : 338 pages
File Size : 51,7 Mb
Release : 2013-01-24
Category : Social Science
ISBN : 9783642329142

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Applied Panel Data Analysis for Economic and Social Surveys by Hans-Jürgen Andreß,Katrin Golsch,Alexander W. Schmidt Pdf

Many economic and social surveys are designed as panel studies, which provide important data for describing social changes and testing causal relations between social phenomena. This textbook shows how to manage, describe, and model these kinds of data. It presents models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All statistical methods are explained in an application-centered style using research examples from scholarly journals, which can be replicated by the reader through data provided on the accompanying website. As all models are compared to each other, it provides valuable assistance with choosing the right model in applied research. The textbook is directed at master and doctoral students as well as applied researchers in the social sciences, psychology, business administration and economics. Readers should be familiar with linear regression and have a good understanding of ordinary least squares estimation. ​