This volume provides a basic framework for using visual data - namely still photographs - as a tool for social analysis. The authors determine the importance of theoretical assumptions in analyzing these data and provide advice on how to use photographs in cognitive, symbolist and structuralist research. The book is richly illustrated with examples ranging from Native American masks to perfume advertisements.
In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license.
The Handbook of Visual Analysis is a rich methodological resource for students, academics, researchers and professionals interested in investigating the visual representation of socially significant issues. The Handbook: Offers a wide-range of methods for visual analysis: content analysis, historical analysis, structuralist analysis, iconography, psychoanalysis, social semiotic analysis, film analysis and ethnomethodology Shows how each method can be applied for the purposes of specific research projects Exemplifies each approach through detailed analyses of a variety of data, including, newspaper images, family photos, drawings, art works and cartoons Includes examples from the authors' own research and professional practice The Handbook of Visual Analysis, which demonstrates the importance of visual data within the social sciences offers an essential guide to those working in a range of disciplines including: media and communication studies, sociology, anthropology, education, psychoanalysis, and health studies.
A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by using animated graphics of the data. Using ViSta: The Visual Statistics System-developed by Forrest Young and Pedro Valero-Mora and available free of charge on the Internet-students can easily create fully interactive visualizations from relevant mathematical statistics, promoting perceptual and cognitive understanding of the data's story. An emphasis is placed on a paradigm for understanding data that is visual, intuitive, geometric, and active, rather than one that relies on convoluted logic, heavy mathematics, systems of algebraic equations, or passive acceptance of results. A companion Web site complements the book by further demonstrating the concept of creating interactive and dynamic graphics. The book provides users with the opportunity to view the graphics in a dynamic way by illustrating how to analyze statistical data and explore the concepts of visual statistics. Visual Statistics addresses and features the following topics: * Why use dynamic graphics? * A history of statistical graphics * Visual statistics and the graphical user interface * Visual statistics and the scientific method * Character-based statistical interface objects * Graphics-based statistical interfaces * Visualization for exploring univariate data This is an excellent textbook for undergraduate courses in data analysis and regression, for students majoring or minoring in statistics, mathematics, science, engineering, and computer science, as well as for graduate-level courses in mathematics. The book is also ideal as a reference/self-study guide for engineers, scientists, and mathematicians. With contributions by highly regarded professionals in the field, Visual Statistics not only improves a student's understanding of statistics, but also builds confidence to overcome problems that may have previously been intimidating.
This book provides ten case studies with concise real-world examples illustrating how MAXQDA is used in practice. In each research example, the authors present their way of using MAXQDA, addressing a variety of practical questions, such as how the coding system was developed, how coded documents were analyzed, what tools were used, and how those tools informed the results. Embedded in the context of each research example, readers can follow analytical processes step-by-step and gain insights into efficient ways to use MAXQDA. Readers can benefit from this book in several ways: - Get inspirations and solutions for their own projects - Avoid pitfalls by considering the lessons learned from each author presented at the end of each chapter - Use the examples in teaching Audience: - All researchers who want to get to learn the potential of qualitative data analysis with MAXQDA - All users of MAXQDA who want to expand their knowledge and skills, no matter if they are novices or experts
Professional-level coverage and techniques for Excel power users Aimed at Excel power users who appreciate logical, clean explanations of techniques, this visual guide features numerous screenshots and easy-to-follow numbered steps in order to show you how to perform professional-level modeling, charting, data sharing, data access, data slicing, and other functions. You'll find super techniques for getting the most out of Excel's statistical and financial functions, Excel PivotTables and PivotCharts, Excel Solver, and more. Demonstrates how to crunch and analyze Excel data the way the professionals do in an uncluttered, visual style Offers a clear look at power-using the new Excel 2013, the latest version of the world's leading spreadsheet application from Microsoft Expands your Excel knowledge and helps you use Excel data more efficiently Explains how to retrieve data from databases; cut, slice, and pivot data using PivotTables; model data and chart data; and use advanced formulas Explores all features and functions in two-color pages packed with screenshots, numbered steps, and other visual graphics that clearly show you how to accomplish tasks Includes practical examples, tips, and advice to help you get the most out of Excel's features and functions Learn the full power of Excel 2013 with this helpful guide!
In this anticipated new edition of Single Case Research Methodology, David L. Gast and Jennifer R. Ledford detail why and how to apply standard principles of single case research methodology to one’s own research or professional project. Using numerous and varied examples, they demonstrate how single case research can be used for research in behavioral and school psychology, special education, speech and communication sciences, language and literacy, occupational therapy, and social work. This thoroughly updated new edition features two entirely new chapters on measurement systems and controversial issues in single subject research, in addition to sample data sheets, graphic displays, and detailed guidelines for conducting visual analysis of graphic data. This book will be an important resource to student researchers, practitioners, and university faculty who are interested in answering applied research questions and objectively evaluating educational and clinical practices.
Best practices and step-by-step instructions for using the Tableau Software toolset Although the Tableau Desktop interface is relatively intuitive, this book goes beyond the simple mechanics of the interface to show best practices for creating effective visualizations for specific business intelligence objectives. It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it. This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software. Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.
Gillian Rose introduces the general themes and recent debates on the meaning of culture and the function of the visual in this introduction to interpreting the visual.
Visual Data Mining—Opening the Black Box Knowledge discovery holds the promise of insight into large, otherwise opaque datasets. Thenatureofwhatmakesaruleinterestingtoauserhasbeendiscussed 1 widely but most agree that it is a subjective quality based on the practical u- fulness of the information. Being subjective, the user needs to provide feedback to the system and, as is the case for all systems, the sooner the feedback is given the quicker it can in?uence the behavior of the system. There have been some impressive research activities over the past few years but the question to be asked is why is visual data mining only now being - vestigated commercially? Certainly, there have been arguments for visual data 2 mining for a number of years – Ankerst and others argued in 2002 that current (autonomous and opaque) analysis techniques are ine?cient, as they fail to - rectly embed the user in dataset exploration and that a better solution involves the user and algorithm being more tightly coupled. Grinstein stated that the “current state of the art data mining tools are automated, but the perfect data mining tool is interactive and highly participatory,” while Han has suggested that the “data selection and viewing of mining results should be fully inter- tive, the mining process should be more interactive than the current state of the 2 art and embedded applications should be fairly automated . ” A good survey on 3 techniques until 2003 was published by de Oliveira and Levkowitz .