Introduction to Information Visualization: Transforming Data into Meaningful Information is for anyone interested in the art and science of communicating data to others. It shows readers how to transform data into something meaningful - information. Applying information visualization in research, service, teaching, and professional life requires a solid understanding of graphic design and the aesthetic along with hands-on skills and knowledge of data principles and software. This book is applicable to students in all domains, to researchers who need to understand how to create graphics that explain their data, and to professionals and administrators for professional development training. Website Designers and Human-Computer Interaction researchers will appreciate the backstory of designing interactive visualizations for the web. Drawing on the author's years of practice and teaching, it bridges the two worlds in ways everyone can participate in the future of information and to appreciate the beautiful in information: oStep-by-step directions in the fundamentals of HTML5, CSS, and d3.js oDesign challenges with fully explained answers oWeb-site support for code samples (JavaScript, d3.js, python), live examples, and a place to build a community of other IV pros oUseful for teaching design to scientists; data to the humanities oGuidance for using the text depending on the class makeup oReview of third-party visualization software, big data trends, and script libraries oGuidance on how to continue in the IV world after graduation This full-color book features graphics and a companion Web site. The online companion site hosts living examples, updates, and errata. You're invited to participate on the site, too, sharing your questions, solutions, and ideas. For most readings, there is a partner design lab. At the conclusion of the course, there is a complete interactive information visualization service documentation for libraries.

It is not lost on commercial organisations that where we live colours how we view ourselves and others. That is why so many now place us into social groups on the basis of the type of postcode in which we live. Social scientists call this practice "commercial sociology". Richard Webber originated Acorn and Mosaic, the two most successful geodemographic classifications. Roger Burrows is a critical interdisciplinary social scientist. Together they chart the origins of this practice and explain the challenges it poses to long-established social scientific beliefs such as: the role of the questionnaire in an era of "big data" the primacy of theory the relationship between qualitative and quantitative modes of understanding the relevance of visual clues to lay understanding. To help readers evaluate the validity of this form of classification, the book assesses how well geodemographic categories track the emergence of new types of residential neighbourhood and subject a number of key contemporary issues to geodemographic modes of analysis.

This book provides an up-to-date picture of the main methods for the quantitative analysis of text.

Popping begins by overviewing the background and the conceptual foundations of the field, introducing the latest developments. He then concentrates on a comprehensive coverage of the traditional thematic approaches of text analysis, followed by the newer developments in semantic and network text analysis methodologies. Finally, the author examines the relationship between content analysis and other kinds of text analysis - from qualitative research, linguistic analysis and information retrieval.

Computer-assisted Text Analysis focuses on the methodological and practical issues of coding and handling data, including sampling, reliability and validity issues, and includes a useful appendix of computer programs for text analysis.

The methods described are applicable across a wide range of disciplines in the social sciences and humanities as well as, for example, practitioners from the fields of political science, journalism., communication, marketing and information systems.

SPSS for Windows is the most widely used computer package for analyzing quantitative data. In a clear, readable, non-technical style, this book teaches beginners how to use the program, input and manipulate data, use descriptive analyses and inferential techniques, including: t-tests, analysis of variance, correlation and regression, nonparametric techniques, and reliability analysis and factor analysis.

The author provides an overview of statistical analysis, and then shows in a simple step-by-step method how to set up an SPSS file in order to run an analysis as well as how to graph and display data. He explains how to use SPSS for all the main statistical approaches you would expect to find in an introductory statistics course.

The book is written for users of Versions 6 and 6.1, but will be equally valuable to users of later versions.

Das Buch bietet einen Einstieg in das Controlling und Management moderner Produktionssysteme mit Hilfe des SAP (R)-ERP-Systems. In praxisnahen Fallbeispielen und zahlreichen Screenshots lernt der Anwender Produktion, Materialplanung und Kostenplanung optimal zu steuern und zu uberwachen. Leicht verstandlich erschliesst sich der Zugang zu den SAP (R)-Modulen CO (R), PP (R), MM (R) und PS (R). ERP-Systeme gehoeren zu den Ankeranwendungen in vielen Branchen, aber auch zum Standardkanon einiger Studiengange. Hier dient das Buch als Lehrunterlage. Die funfte Auflage wurde, basierend auf dem neuesten IDES (R)-Release ECC (R)6.0, aktualisiert und erweitert.

Partendo dai temi cari e mai completamente risolti della traduttologia, che si potrebbero esemplificare nell'affermazione per cui la pratica traduttiva e da sempre alla ricerca di una teoria che la spieghi, la modelli e le dia un fondamento scientifico, questo lavoro ha l'ambizione di fornire, adottando l'approccio semiotico della scuola di Parigi, una nuova sistematizzazione della traduzione in quanto concetto, pratica e testo. Le relazioni identitarie e veridittive, articolate nel quadrato semiotico, determinano le condizioni ontologiche della traduzione; la schematizzazione narrativa modellizza la pratica traduttiva ed esplicita le competenze del traduttore, gli aspetti manipolativi e le condizioni aletiche ed etiche insiti nella traduzione. L'analisi si sposta poi su terreni piu empirici e la proposta teorica si misura con il testo tradotto; su quest'ultimo si identificano i rapporti identita-alterita, la dimensione assiologica e la prensione timica del traduttore. La prospettiva generativa permette di situarsi in una dimensione epistemica e metodologica piu ampia, che al contempo impone una riflessione sulle condizioni di felicita specifiche della traduttologia.

This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the "meaning" of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors' approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science. First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series, C = XXT, where Xrepresents a rectangular matrix of N rows and L columns and XT represents the transverse matrix of X. Because C is symmetric, namely, C = CT, it can be converted to a diagonal matrix of eigenvalues by a similarity transformation-1 = SCST using an orthogonal matrix S. When N is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation). Then the RMT-PCA applied to high-frequency stock prices in Japanese and American markets is dealt with. This approach proves its effectiveness in extracting "trendy" business sectors of the financial market over the prescribed time scale. In this case, X consists of N stock- prices of lengthL, and the correlation matrix C is an N by N square matrix, whose element at the i-th row and j-th column is the inner product of the price time series of the length L of the i-th stock and the j-th stock of the equal length L. Next, the RMT-test is applied to measure randomness of various random number generators, including algorithmically generated random numbers and physically generated random numbers. The book concludes by demonstrating two application of the RMT-test: (1) a comparison of hash functions, and (2) stock prediction by means of randomness.