Principles Of Statistical Data Handling
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Principles Of Statistical Data Handling
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Author : Fred Davidson
language : en
Publisher:
Release Date : 1996
Principles Of Statistical Data Handling written by Fred Davidson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Educational statistics categories.
This volume demonstrates how to input, manipulate and debug data to make substantive analysis easier and more accurate. Using a series of principles, universal concepts that apply no matter what the data-gathering context or computer software, Fred Davidson presents a situation or a problem, suggests how it might be resolved and demonstrates the implementation of each principle as it appears in the command languages of SAS and SPSS.
Principles Of Statistical Data Handling
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Author : Fred Davidson
language : en
Publisher: SAGE Publications, Incorporated
Release Date : 1996-04-09
Principles Of Statistical Data Handling written by Fred Davidson and has been published by SAGE Publications, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-04-09 with Education categories.
ABOUT THE APPROACH "I like the stress on a ′principled approach′ to data handling. The author makes clear that data analysts need to be thoughtful, careful, and reflective; data handling is not viewed as simply a mechanical or routine activity." --George Engelhard Jr., Emory University GENERAL "Principles of Statistical Data Handling deals with the most neglected aspect of implementing a quantitative research design, that is preparing the data for statistical analysis. Because this part of the process is so often neglected it is the most common source of trouble when a quantitative research project crashes, produces gibberish, and has to be done all over again. Remarkably, the author writes an interesting and easy-to-read book on what might seem an irredeemably dreary and technical topic. I will recommend this book to almost every one of my students who plans to do a dissertation using quantitative data." W. Paul Vogt, State University of New York, Albany "Many of the topics and strategies covered in this text are very realistic, and most of us that have been involved in data analysis over the years can relate to the data handling problems mentioned in the text; the author has done an excellent job of sharing his wisdom from many years of practical work as a data analyst." --George Engelhard Jr., Emory University ABOUT THE WRITING STYLE "The writing style is clearly informal. The author speaks to the reader as a good teacher speaks to a student." --Robert F. DeVellis, The University of North Carolina, Chapel Hill "There is a delightful humor that comes through in this book and a playfulness that I enjoyed. The pace and level is appropriate for an introduction to data handling." --John W. Creswell, University of Nebraska, Lincoln ABOUT THE PEDAGOGY "The discussion questions are very, very good. I particularly like the idea of suggesting that the reader/student interact with some ′outsiders.′" --Carl J. Huberty, The University of Georgia Faulty data can lead to faulty conclusions, and because data often concern people--that can mean faulty conclusions about people. Aimed at helping readers understand the principles of data handling so that they can make better use of computer data in their research and studies, Principles of Statistical Data Handling shows readers how to input, manipulate, and debug their data to make substantive analysis easier and more accurate. Using a series of principles, universal concepts that apply no matter what the data gathering context or computer software, author Fred Davidson presents a situation or a problem, suggests how it might be resolved, and demonstrates the implementation of each principle as it appears in the command languages of SAS and SPSS. This volume is essential for graduate courses in data analysis or research methods taught out of psychology, education, and sociology departments. Researchers in these areas who want to brush-up on their techniques will also find Principles of Statistical Data Handling an indispensable book.
Data Management And Statistical Analysis Techniques
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Author : Ronin Myers
language : en
Publisher: Scientific e-Resources
Release Date : 2019-05-19
Data Management And Statistical Analysis Techniques written by Ronin Myers and has been published by Scientific e-Resources this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-19 with categories.
Principles Of Data Management And Presentation
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Author : John P. Hoffmann
language : en
Publisher: Univ of California Press
Release Date : 2017-07-03
Principles Of Data Management And Presentation written by 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 Reference categories.
Why research? -- Developing research questions -- Data -- Principles of data management -- Finding and using secondary data -- Primary and administrative data -- Working with missing data -- Principles of data presentation -- Designing tables for data presentations -- Designing graphics for data presentations
Statistical Confidentiality
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Author : George T. Duncan
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-22
Statistical Confidentiality written by George T. Duncan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-22 with Social Science categories.
Because statistical confidentiality embraces the responsibility for both protecting data and ensuring its beneficial use for statistical purposes, those working with personal and proprietary data can benefit from the principles and practices this book presents. Researchers can understand why an agency holding statistical data does not respond well to the demand, “Just give me the data; I’m only going to do good things with it.” Statisticians can incorporate the requirements of statistical confidentiality into their methodologies for data collection and analysis. Data stewards, caught between those eager for data and those who worry about confidentiality, can use the tools of statistical confidentiality toward satisfying both groups. The eight chapters lay out the dilemma of data stewardship organizations (such as statistical agencies) in resolving the tension between protecting data from snoopers while providing data to legitimate users, explain disclosure risk and explore the types of attack that a data snooper might mount, present the methods of disclosure risk assessment, give techniques for statistical disclosure limitation of both tabular data and microdata, identify measures of the impact of disclosure limitation on data utility, provide restricted access methods as administrative procedures for disclosure control, and finally explore the future of statistical confidentiality.
Practical Applications Of Data Processing Algorithms And Modeling
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Author : Whig, Pawan
language : en
Publisher: IGI Global
Release Date : 2024-04-29
Practical Applications Of Data Processing Algorithms And Modeling written by Whig, Pawan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Handbook Of Computational Social Science For Policy
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Author : Eleonora Bertoni
language : en
Publisher: Springer Nature
Release Date : 2023-01-23
Handbook Of Computational Social Science For Policy written by Eleonora Bertoni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-23 with Computers categories.
This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields. To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holdingdata that can be used to study social sciences and are interested in achieving a policy impact.
The Open Handbook Of Linguistic Data Management
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Author : Andrea L. Berez-Kroeker
language : en
Publisher: MIT Press
Release Date : 2022-01-18
The Open Handbook Of Linguistic Data Management written by Andrea L. Berez-Kroeker and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-18 with Language Arts & Disciplines categories.
A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.
Technometrics
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Author :
language : en
Publisher:
Release Date : 1997
Technometrics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Experimental design categories.