Handbook of Statistical Data Editing and Imputation by
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.
Data Analysis
Data analysis is a process of testing the information against theoretical constructions. These can be as organized as a hypothesis or as general as a theoretical framework. It is also a process of bringing order, structure, and meaning to the mass of collected data what can be called making meaning.
•There are two sides to analysis, one involves following the standards of a dispelling. In humanities, this involves the application of empathy alongside critical thinking. In science, there is an element of puzzle solving.
•Data visualization is a creative process that makes a meaningful story often for publication out of a mass of results.
•Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes. (ref)
Qualitative Data Analysis by
The Third Edition of Miles & Huberman′s classic research methods text is updated and streamlined by Johnny Saldaña, author of The Coding Manual for Qualitative Researchers. Several of the data display strategies from previous editions are now presented in re-envisioned and reorganized formats to enhance reader accessibility and comprehension. The Third Edition′s presentation of the fundamentals of research design and data management is followed by five distinct methods of analysis: exploring, describing, ordering, explaining, and predicting. Miles and Huberman′s original research studies are profiled and accompanied with new examples from Saldaña′s recent qualitative work. The book′s most celebrated chapter, "Drawing and Verifying Conclusions," is retained and revised, and the chapter on report writing has been greatly expanded, and is now called "Writing About Qualitative Research." Comprehensive and authoritative, Qualitative Data Analysis has been elegantly revised for a new generation of qualitative researchers.
Benefits of Data Management click here.
Data Management Using Stata by
Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis.
A Practical Introduction to Qualitative Research by
This title provides a one-stop resource for all those approaching qualitative research for the first time, as well as those revisiting core concepts and issues. It presents a comprehensive overview of this developing field of inquiry, combined with practical, hands-on advice on how to conduct a successful qualitative study.
Metadata is a set of data that describes and gives information about other data. It can be as simple as the author, date and title. With data it typically involves description of type of data collection methods, variables. the links below have examples
Or is data [information] that provides information about other data.
Metadata Fundamentals for All Librarians by
Metadata, or data about data, is used to organize and access information in an effective way. From cataloguing to organizing archives, metadata helps front-line librarians provide customers with a direct path to information. In this text, Priscilla Caplan presents a comprehensive description of the various forms of metadata, its applications, and how librarians can put it to work.
There are two reasons, Researchers tell us that they do data management
New Trends in Qualitative and Quantitative Methods in Libraries - Proceedings of the International Conference on Qqml2010 by
An Autodesk Official Press guide to the powerful mechanical design software Autodesk Inventor has been used to design everything from cars and airplanes to appliances and furniture. This comprehensive guide to Inventor and Inventor LT features real-world workflows and work environments, and is packed with practical tutorials that focus on teaching Inventor tips, tricks, and techniques. Additionally, you can download datasets to jump in and practice on any exercise. This reference and tutorial explains key interface conventions, capabilities, tools, and techniques, including design concepts and application, parts design, assemblies and subassemblies, weldment design, and the use of Design Accelerators and Design Calculators. There′s also detailed coverage of design tactics for large assemblies, effective model design for various industries, strategies for effective data and asset sharing, using 2D and 3D data from other CAD systems, and improving designs by incorporating engineering principles. Uses real-world sample projects so you can quickly grasp the interface, tools, and processes Features detailed documentation on everything from project set up to simple animations and documentation for exploded views, sheet metal flat patterns, plastic part design, and more Covers crucial productivity-boosting tools, iLogic, data exchange, the Frame Generator, Inventor Studio visualization tools, dynamic simulation and stress analysis features, and routed systems features Downloadable datasets let you jump into the step-by-step tutorials anywhere Mastering Autodesk Inventor and Autodesk Inventor LT is the essential, comprehensive training guide for this powerful software.
Qualitative Data Analysis by
In this fully updated and expanded second edition, Carol Grbich provides a guide through current issues in the analysis of qualitative data. Packed with detailed examples, a glossary, further reading lists and a section on writing up, this book is exactly what you need to get you started in qualitative research. The new edition covers analytical approaches including: - grounded theory - classical, existential and hermeneutic phenomenology - feminist research including memory work - classical, auto- and cyberethnography as well as ethnodrama - content, narrative, conversation and discourse analysis - visual interpretation - semiotic, structural and poststructural analyses A one-stop-shop for students new to qualitative data analysis! Available with Perusall--an eBook that makes it easier to prepare for classPerusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Qualitative Data Analysis by
Qualitative Data Analysis with ATLAS.ti is the very first book designed to guide you step-by-step through your research project using ATLAS.ti. In the book, you will find clear, practical advice on preparing your data, setting up a new project in ATLAS.ti, developing a coding system, asking questions, finding answers and preparing your results. The book features: - methodological as well as technical advice - numerous practical exercises and examples - screenshots showing you each stage of analysis - a companion website with online tutorials and data sets Susanne Friese teaches qualitative methods at the University of Hanover and at various PhD schools, provides training and consultancy for ATLAS.ti at the intersection between developers and users.
Quantitative Methods by
Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods in Psychology is the complete tool box to deliver the most valid and generalizable answers to today's complex research questions. It is aone-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences.Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies.Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chaptersassociated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
An Introduction to the Basics of Research Data Management (YouTube video by Louise Patterton)
A great deal of energy has been put into defining the difference between qualitative and qualitative data. Different authors have a definition that varies across fields. We would say that for the purposes of helping you work with your data, it does not matter and can be a distraction.
Data is that which you can use to create a research result from or which underlays the result. It's the information that you, as a researcher in a field of inquiry,can legitimately point to in making arguments and coming to conclusions. It, in other words, the stuff you study. Whatever that stuff is so long as it gets you to a result, its data.
For the purposes of data services, Quantitative data is that data which you can apply statistical tests too. It matters immensely if it is ordinal, or not. It's important to check if its normally distributed. In other words, does it meet the assumption that underlay the particular test? However, even if its numbers, if you can't use stats then it not useful to see it as qualitative.
Qualitative data is that data to which you can apply the processes and theories of qualitative inquiry.This means that if you are doing policy work, a website is a data, if you are doing computer science, the download stats of that website is data.
If you feel our definition is too basic then take a look at the video. This was made by the NEDDICK group of mainly data librarians of which wits is a member, We are scattered around the country. So if you need help and you are not at wits remember we can always refer you to a data librarian near you. For a lot more useful information from NeDICC, Click here