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Social Science Data File Directory Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Social Science Data File Directory book. This book definitely worth reading, it is an incredibly well-written.
Author : Anonim
Publisher : Unknown
Page : 394 pages
File Size : 45,8 Mb
Release : 1975
Category : Bibliographical services
ISBN : STANFORD:36105117274444
Author : Vivian S. Sessions
Publisher : Unknown
Page : 330 pages
File Size : 55,9 Mb
Release : 1974
Category : Information storage and retrieval systems
ISBN : UOM:39015030436433
International listing of computer data bases and their data components. Alphabetical arrangement by institutions or agencies. Entries include address, telephone number, persons in charge, subject, details about the computer, storage media, output media, data products, and access information. Indexes by subject, institution, personnel, and geographical location.
Author : Anonim
Publisher : Unknown
Page : 520 pages
File Size : 43,8 Mb
Release : 1975
Category : United States
ISBN : UOM:39015083679897
Author : Brian J. Fogarty
Publisher : SAGE Publications Limited
Page : 566 pages
File Size : 45,6 Mb
Release : 2023-03-11
Category : Social Science
ISBN : 9781529614220
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. Gradually introducing applied statistics and the language and functionality of R and R Studio software, it uses examples from across the social sciences to show students how to apply abstract statistical and methodological principles to their own work. Maintaining a student-friendly pace, it goes beyond a normal introductory statistics book and shows students where data originates and how to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives students not only the tools they need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what they have learned.
Author : Kosuke Imai,Lori D. Bougher
Publisher : Princeton University Press
Page : 472 pages
File Size : 53,8 Mb
Release : 2021-03-16
Category : Social Science
ISBN : 9780691191294
The Stata edition of the groundbreaking textbook on data analysis and statistics for the social sciences and allied fields Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as business, economics, education, political science, psychology, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the Stata statistical software and interpret the results—it emphasizes hands-on learning, not paper-and-pencil statistics. More than fifty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in classrooms around the world, this one-of-a-kind textbook features numerous additional data analysis exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including business, economics, education, psychology, political science, sociology, public policy, and data science Provides hands-on instruction using Stata, not paper-and-pencil statistics Includes more than fifty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
Author : National Referral Center (U.S.)
Publisher : Unknown
Page : 230 pages
File Size : 49,9 Mb
Release : 1965
Category : Information services
ISBN : STANFORD:36105041159604
Author : Quan Li
Publisher : Oxford University Press
Page : 369 pages
File Size : 41,6 Mb
Release : 2018
Category : Business & Economics
ISBN : 9780190656218
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.
Author : Allen Kent
Publisher : CRC Press
Page : 426 pages
File Size : 44,7 Mb
Release : 1986-02-28
Category : Language Arts & Disciplines
ISBN : 0824720407
"The Encyclopedia of Library and Information Science provides an outstanding resource in 33 published volumes with 2 helpful indexes. This thorough reference set--written by 1300 eminent, international experts--offers librarians, information/computer scientists, bibliographers, documentalists, systems analysts, and students, convenient access to the techniques and tools of both library and information science. Impeccably researched, cross referenced, alphabetized by subject, and generously illustrated, the Encyclopedia of Library and Information Science integrates the essential theoretical and practical information accumulating in this rapidly growing field."
Author : David J. Makowski
Publisher : Unknown
Page : 212 pages
File Size : 47,6 Mb
Release : 1980
Category : Continuing education
ISBN : OSU:32435008707416
Author : Ryan Kennedy,Philip D. Waggoner
Publisher : CRC Press
Page : 198 pages
File Size : 48,9 Mb
Release : 2021-02-23
Category : Mathematics
ISBN : 9781000353853
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.
Author : Criminal Justice Archive and Information Network
Publisher : Unknown
Page : 484 pages
File Size : 51,7 Mb
Release : 1986
Category : Crime
ISBN : UCAL:B4351816
Author : Uwe Engel,Anabel Quan-Haase,Sunny Xun Liu,Lars Lyberg
Publisher : Taylor & Francis
Page : 434 pages
File Size : 43,5 Mb
Release : 2021-11-10
Category : Computers
ISBN : 9781000448597
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 second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into 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 scientific and engineering sectors.
Author : Bernie Hogan
Publisher : SAGE
Page : 334 pages
File Size : 54,8 Mb
Release : 2022-11-23
Category : Social Science
ISBN : 9781529737172
From Social Science to Data Science is a fundamental guide to scaling up and advancing your programming skills in Python. From beginning to end, this book will enable you to understand merging, accessing, cleaning and interpreting data whilst gaining a deeper understanding of computational techniques and seeing the bigger picture. With key features such as tables, figures, step-by-step instruction and explanations giving a wider context, Hogan presents a clear and concise analysis of key data collection and skills in Python.
Author : Steven Lloyd Wilson
Publisher : Cambridge University Press
Page : 185 pages
File Size : 53,5 Mb
Release : 2022-11-17
Category : Social Science
ISBN : 9781108755573
Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.
Author : Rachel A. Gordon
Publisher : Routledge
Page : 567 pages
File Size : 52,8 Mb
Release : 2015-03-17
Category : Social Science
ISBN : 9781317607113
Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: •interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. •thorough integration of teaching statistical theory with teaching data processing and analysis. •teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.
