An Introduction To Data Management In The Behavioral And Social Sciences
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An Introduction To Data Management In The Behavioral And Social Sciences
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Author : Sheldon Blackman
language : en
Publisher: John Wiley & Sons
Release Date : 1971
An Introduction To Data Management In The Behavioral And Social Sciences written by Sheldon Blackman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Sciences sociales - Informatique categories.
An Introduction To Data Management In The Behavioral And Social Sciences
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Author : Sheldon Blackman
language : en
Publisher:
Release Date : 1971
An Introduction To Data Management In The Behavioral And Social Sciences written by Sheldon Blackman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Computer science categories.
Textbook on computerised statistical analysis of numeric data for social research purposes - covers relevant theoretical and technical aspects of EDP, statistical method, research methodology, etc. Diagrams and references.
Principles Of Data Management And Presentation
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Author : Dr. John P. Hoffmann
language : en
Publisher: Univ of California Press
Release Date : 2017-07-03
Principles Of Data Management And Presentation written by Dr. John P. Hoffmann and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-03 with Social Science categories.
The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences. Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including: • how to narrow a research topic to a specific research question • how to access and organize data that are useful for answering a research question • how to use software such as Stata, SPSS, and SAS to manage data • how to present data so that they convey a clear and effective message A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab.
Introduction To Quantitative Data Analysis In The Behavioral And Social Sciences
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Author : Michael J. Albers
language : en
Publisher: John Wiley & Sons
Release Date : 2017-04-03
Introduction To Quantitative Data Analysis In The Behavioral And Social Sciences written by Michael J. Albers and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-03 with Mathematics categories.
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.
Big Data And Social Science
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Author : Ian Foster
language : en
Publisher: CRC Press
Release Date : 2020-11-17
Big Data And Social Science written by Ian Foster and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Mathematics categories.
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
Introduction To Data Science For Social And Policy Research
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Author : Jose Manuel Magallanes Reyes
language : en
Publisher: Cambridge University Press
Release Date : 2017-09-21
Introduction To Data Science For Social And Policy Research written by Jose Manuel Magallanes Reyes 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 2017-09-21 with Mathematics categories.
This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
Data Management For Social Scientists
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Author : Nils B. Weidmann
language : en
Publisher: Cambridge University Press
Release Date : 2023-03-09
Data Management For Social Scientists written by Nils B. Weidmann 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 2023-03-09 with Social Science categories.
The 'data revolution' offers many new opportunities for research in the social sciences. Increasingly, social and political interactions can be recorded digitally, leading to vast amounts of new data available for research. This poses new challenges for organizing and processing research data. This comprehensive introduction covers the entire range of data management techniques, from flat files to database management systems. It demonstrates how established techniques and technologies from computer science can be applied in social science projects, drawing on a wide range of different applied examples. This book covers simple tools such as spreadsheets and file-based data storage and processing, as well as more powerful data management software like relational databases. It goes on to address advanced topics such as spatial data, text as data, and network data. This book is one of the first to discuss questions of practical data management specifically for social science projects. This title is also available as Open Access on Cambridge Core.
Data Mining For The Social Sciences
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Author : Paul Attewell
language : en
Publisher: Univ of California Press
Release Date : 2015-04-30
Data Mining For The Social Sciences written by Paul Attewell and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-30 with Social Science categories.
We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.
The Behavioral And Social Sciences
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 1988-02-01
The Behavioral And Social Sciences written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-02-01 with Science categories.
This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.
Analysis And Modeling Of Complex Data In Behavioral And Social Sciences
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Author : Donatella Vicari
language : en
Publisher: Springer
Release Date : 2014-07-05
Analysis And Modeling Of Complex Data In Behavioral And Social Sciences written by Donatella Vicari and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-05 with Mathematics categories.
This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate. The challenging proposals provide a connection between statistical methodology and the social domain with particular attention to computational issues in order to effectively address complicated data analysis problems. The papers in this volume stem from contributions initially presented at the joint international meeting JCS-CLADAG held in Anacapri (Italy) where the Japanese Classification Society and the Classification and Data Analysis Group of the Italian Statistical Society had a stimulating scientific discussion and exchange.
