Download or read book Exploring Data written by Catherine Marsh and published by Polity. This book was released on 2008 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exploring Data written by Catherine Marsh and published by . This book was released on 1988 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exploring Data An Introduction to Data Analysis for Social Scientists written by Jane; Marsh Elliott (Catherine) and published by Polity. This book was released on 2009 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences written by Michael J. Albers and published by John Wiley & Sons. This book was released on 2017-02-21 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
Download or read book Exploratory Data Analysis written by Frederick Hartwig and published by SAGE. This book was released on 1979 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the underlying principles, central concepts, and basic techniques for conducting and understanding exploratory data analysis - with numerous social science examples.
Download or read book Introducing Data Analysis for Social Scientists written by David Rose and published by . This book was released on 1993-01-01 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2016-08-10 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
Download or read book Statistical Inference via Data Science A ModernDive into R and the Tidyverse written by Chester Ismay and published by CRC Press. This book was released on 2019-12-23 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.
Download or read book Beginning Statistics written by Ian Diamond and published by SAGE. This book was released on 2013-02-26 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: `The clarity, simplicity and use of many practical examples makes this book very useful, primarily for under- and postgraduate students′ - Journal of Biosocial Science With an emphasis on description, examples, graphs and displays rather than statistical formulae, this book is the ideal introductory guide for students across the social sciences. It shows how all students can understand the basic ideas of statistics at a level appropriate with being a good social scientist. The authors explain the right ways to present data, how to describe a set of data using summary statistics and how to infer what is going on in a population when all you have to go on is the sample. The book uses small data sets to help students understand the basic principles, and no mathematics or statistical background is assumed.
Download or read book Data Analytics for the Social Sciences written by G. David Garson and published by Routledge. This book was released on 2021-11-30 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Humanities Data Analysis written by Folgert Karsdorp and published by Princeton University Press. This book was released on 2021-01-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations
Download or read book Making Sense of Data I written by Glenn J. Myatt and published by John Wiley & Sons. This book was released on 2014-07-02 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “...a well-written book on data analysis and data mining that provides an excellent foundation...” —CHOICE “This is a must-read book for learning practical statistics and data analysis...” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available TraceisTM software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.
Download or read book Quantitative Data Analysis written by Donald J. Treiman and published by John Wiley & Sons. This book was released on 2014-01-30 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible introduction to quantitative dataanalysis, concentrating on the key issues facing those new toresearch, such as how to decide which statistical procedure issuitable, and how to interpret the subsequent results. Each chapterincludes illustrative examples and a set of exercises that allowsreaders to test their understanding of the topic. The book, writtenfor graduate students in the social sciences, public health, andeducation, offers a practical approach to making sociological senseout of a body of quantitative data. The book also will be useful tomore experienced researchers who need a readily accessible handbookon quantitative methods. The author has posted stata files, updates and data sets athis websitehttp://tinyurl.com/Treiman-stata-files-data-sets.
