[PDF] Visualization And Interpretation eBook

Author : Johanna Drucker
Publisher : MIT Press
Page : 205 pages
File Size : 23,26 MB
Release : 2020-11-10
Category : Social Science
ISBN : 0262361167

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An analysis of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts. In the several decades since humanists have taken up computational tools, they have borrowed many techniques from other fields, including visualization methods to create charts, graphs, diagrams, maps, and other graphic displays of information. But are these visualizations actually adequate for the interpretative approach that distinguishes much of the work in the humanities? Information visualization, as practiced today, lacks the interpretivist frameworks required for humanities-oriented methodologies. In this book, Johanna Drucker continues her interrogation of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts.

Author : Kieran Healy
Publisher : Princeton University Press
Page : 292 pages
File Size : 28,73 MB
Release : 2018-12-18
Category : Social Science
ISBN : 0691181624

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An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Author : Martin Engebretsen
Publisher : Amsterdam University Press
Page : pages
File Size : 48,7 MB
Release : 2020-03-21
Category : Computers
ISBN : 9463722904

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Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

Author : Tamara Munzner
Publisher : CRC Press
Page : 422 pages
File Size : 47,93 MB
Release : 2014-12-01
Category : Business & Economics
ISBN : 1466508930

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Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques

Author : Guilherme D. Garcia
Publisher : Taylor & Francis
Page : 287 pages
File Size : 39,67 MB
Release : 2021-05-30
Category : Business & Economics
ISBN : 1000394581

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This introduction to visualization techniques and statistical models for second language research focuses on three types of data (continuous, binary, and scalar), helping readers to understand regression models fully and to apply them in their work. Garcia offers advanced coverage of Bayesian analysis, simulated data, exercises, implementable script code, and practical guidance on the latest R software packages. The book, also demonstrating the benefits to the L2 field of this type of statistical work, is a resource for graduate students and researchers in second language acquisition, applied linguistics, and corpus linguistics who are interested in quantitative data analysis.

Author : Edward R. Tufte
Publisher :
Page : 197 pages
File Size : 39,3 MB
Release : 2001-01-01
Category : Mathematics
ISBN : 9780961392147

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Graphical practice. Theory of data graphics.

Author : Nilanjan Dey
Publisher : Springer
Page : 163 pages
File Size : 22,9 MB
Release : 2018-05-23
Category : Science
ISBN : 3319899236

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This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.

Author : Gregg Hartvigsen
Publisher : Columbia University Press
Page : 245 pages
File Size : 47,6 MB
Release : 2014-02-18
Category : Education
ISBN : 0231537042

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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.