Author: American Statistical Association. Section on Statistical Graphics
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 126
Book Description
Proceedings of the Section on Statistical Graphics
Author: American Statistical Association. Section on Statistical Graphics
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 126
Book Description
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 126
Book Description
Statistical Graphics for Visualizing Multivariate Data
Author: William G. Jacoby
Publisher: SAGE
ISBN: 9780761908999
Category : Mathematics
Languages : en
Pages : 116
Book Description
Jacoby explores a variety of graphical displays that are useful for visualising multivariate data, and introduces the concept of a 'data space'. Several methods for coding information directly into the plotting symbols are explained.
Publisher: SAGE
ISBN: 9780761908999
Category : Mathematics
Languages : en
Pages : 116
Book Description
Jacoby explores a variety of graphical displays that are useful for visualising multivariate data, and introduces the concept of a 'data space'. Several methods for coding information directly into the plotting symbols are explained.
Statistics
Author: Thomas Hill
Publisher: StatSoft, Inc.
ISBN: 9781884233593
Category : Mathematics
Languages : en
Pages : 854
Book Description
This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ("consumer") of these methods.
Publisher: StatSoft, Inc.
ISBN: 9781884233593
Category : Mathematics
Languages : en
Pages : 854
Book Description
This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ("consumer") of these methods.
The Grammar of Graphics
Author: Leland Wilkinson
Publisher: Springer Science & Business Media
ISBN: 1475731000
Category : Computers
Languages : en
Pages : 415
Book Description
Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.
Publisher: Springer Science & Business Media
ISBN: 1475731000
Category : Computers
Languages : en
Pages : 415
Book Description
Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.
Information Visualization
Author: Andreas Kerren
Publisher: Springer
ISBN: 3540709568
Category : Computers
Languages : en
Pages : 184
Book Description
This book is the outcome of the Dagstuhl Seminar on "Information Visualization -- Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data. This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: There are general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. And specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.
Publisher: Springer
ISBN: 3540709568
Category : Computers
Languages : en
Pages : 184
Book Description
This book is the outcome of the Dagstuhl Seminar on "Information Visualization -- Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data. This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: There are general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. And specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.
A History of Data Visualization and Graphic Communication
Author: Michael Friendly
Publisher: Harvard University Press
ISBN: 0674259041
Category : Science
Languages : en
Pages : 337
Book Description
A comprehensive history of data visualization—its origins, rise, and effects on the ways we think about and solve problems. With complex information everywhere, graphics have become indispensable to our daily lives. Navigation apps show real-time, interactive traffic data. A color-coded map of exit polls details election balloting down to the county level. Charts communicate stock market trends, government spending, and the dangers of epidemics. A History of Data Visualization and Graphic Communication tells the story of how graphics left the exclusive confines of scientific research and became ubiquitous. As data visualization spread, it changed the way we think. Michael Friendly and Howard Wainer take us back to the beginnings of graphic communication in the mid-seventeenth century, when the Dutch cartographer Michael Florent van Langren created the first chart of statistical data, which showed estimates of the distance from Rome to Toledo. By 1786 William Playfair had invented the line graph and bar chart to explain trade imports and exports. In the nineteenth century, the “golden age” of data display, graphics found new uses in tracking disease outbreaks and understanding social issues. Friendly and Wainer make the case that the explosion in graphical communication both reinforced and was advanced by a cognitive revolution: visual thinking. Across disciplines, people realized that information could be conveyed more effectively by visual displays than by words or tables of numbers. Through stories and illustrations, A History of Data Visualization and Graphic Communication details the 400-year evolution of an intellectual framework that has become essential to both science and society at large.
Publisher: Harvard University Press
ISBN: 0674259041
Category : Science
Languages : en
Pages : 337
Book Description
A comprehensive history of data visualization—its origins, rise, and effects on the ways we think about and solve problems. With complex information everywhere, graphics have become indispensable to our daily lives. Navigation apps show real-time, interactive traffic data. A color-coded map of exit polls details election balloting down to the county level. Charts communicate stock market trends, government spending, and the dangers of epidemics. A History of Data Visualization and Graphic Communication tells the story of how graphics left the exclusive confines of scientific research and became ubiquitous. As data visualization spread, it changed the way we think. Michael Friendly and Howard Wainer take us back to the beginnings of graphic communication in the mid-seventeenth century, when the Dutch cartographer Michael Florent van Langren created the first chart of statistical data, which showed estimates of the distance from Rome to Toledo. By 1786 William Playfair had invented the line graph and bar chart to explain trade imports and exports. In the nineteenth century, the “golden age” of data display, graphics found new uses in tracking disease outbreaks and understanding social issues. Friendly and Wainer make the case that the explosion in graphical communication both reinforced and was advanced by a cognitive revolution: visual thinking. Across disciplines, people realized that information could be conveyed more effectively by visual displays than by words or tables of numbers. Through stories and illustrations, A History of Data Visualization and Graphic Communication details the 400-year evolution of an intellectual framework that has become essential to both science and society at large.
Handbook of Computational Statistics
Author: James E. Gentle
Publisher: Springer Science & Business Media
ISBN: 3642215513
Category : Computers
Languages : en
Pages : 1180
Book Description
The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.
Publisher: Springer Science & Business Media
ISBN: 3642215513
Category : Computers
Languages : en
Pages : 1180
Book Description
The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.
Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery
Author: Boris Kovalerchuk
Publisher: Springer Nature
ISBN: 3030931196
Category : Technology & Engineering
Languages : en
Pages : 671
Book Description
This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.
Publisher: Springer Nature
ISBN: 3030931196
Category : Technology & Engineering
Languages : en
Pages : 671
Book Description
This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.
Graphics of Large Datasets
Author: Antony Unwin
Publisher: Springer Science & Business Media
ISBN: 0387379770
Category : Computers
Languages : en
Pages : 276
Book Description
This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases, or large in numbers of variables, or large in both. All ideas are illustrated with displays from analyses of real datasets and the importance of interpreting displays effectively is emphasized. Graphics should be drawn to convey information and the book includes many insightful examples. New approaches to graphics are needed to visualize the information in large datasets and most of the innovations described in this book are developments of standard graphics. The book is accessible to readers with some experience of drawing statistical graphics.
Publisher: Springer Science & Business Media
ISBN: 0387379770
Category : Computers
Languages : en
Pages : 276
Book Description
This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases, or large in numbers of variables, or large in both. All ideas are illustrated with displays from analyses of real datasets and the importance of interpreting displays effectively is emphasized. Graphics should be drawn to convey information and the book includes many insightful examples. New approaches to graphics are needed to visualize the information in large datasets and most of the innovations described in this book are developments of standard graphics. The book is accessible to readers with some experience of drawing statistical graphics.
Exploratory Data Analysis with MATLAB
Author: Wendy L. Martinez
Publisher: CRC Press
ISBN: 1439812217
Category : Business & Economics
Languages : en
Pages : 525
Book Description
Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB®, Second Edition uses numerous examples and applications to show how the methods are used in practice. New to the Second Edition Discussions of nonnegative matrix factorization, linear discriminant analysis, curvilinear component analysis, independent component analysis, and smoothing splines An expanded set of methods for estimating the intrinsic dimensionality of a data set Several clustering methods, including probabilistic latent semantic analysis and spectral-based clustering Additional visualization methods, such as a rangefinder boxplot, scatterplots with marginal histograms, biplots, and a new method called Andrews’ images Instructions on a free MATLAB GUI toolbox for EDA Like its predecessor, this edition continues to focus on using EDA methods, rather than theoretical aspects. The MATLAB codes for the examples, EDA toolboxes, data sets, and color versions of all figures are available for download at http://pi-sigma.info
Publisher: CRC Press
ISBN: 1439812217
Category : Business & Economics
Languages : en
Pages : 525
Book Description
Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB®, Second Edition uses numerous examples and applications to show how the methods are used in practice. New to the Second Edition Discussions of nonnegative matrix factorization, linear discriminant analysis, curvilinear component analysis, independent component analysis, and smoothing splines An expanded set of methods for estimating the intrinsic dimensionality of a data set Several clustering methods, including probabilistic latent semantic analysis and spectral-based clustering Additional visualization methods, such as a rangefinder boxplot, scatterplots with marginal histograms, biplots, and a new method called Andrews’ images Instructions on a free MATLAB GUI toolbox for EDA Like its predecessor, this edition continues to focus on using EDA methods, rather than theoretical aspects. The MATLAB codes for the examples, EDA toolboxes, data sets, and color versions of all figures are available for download at http://pi-sigma.info