Graphics of Large Datasets Visualizing a Million /

Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day? 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. Data visualization is...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Unwin, Antony (Συγγραφέας), Theus, Martin (Συγγραφέας), Hofmann, Heike (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York, 2006.
Σειρά:Statistics and Computing,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Unwin, Antony.  |e author. 
245 1 0 |a Graphics of Large Datasets  |h [electronic resource] :  |b Visualizing a Million /  |c by Antony Unwin, Martin Theus, Heike Hofmann. 
264 1 |a New York, NY :  |b Springer New York,  |c 2006. 
300 |a XIII, 271 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Statistics and Computing,  |x 1431-8784 
505 0 |a Basics -- Statistical Graphics -- Scaling Up Graphics -- Interacting with Graphics -- Applications -- Multivariate Categorical Data — Mosaic Plots -- Rotating Plots -- Multivariate Continuous Data — Parallel Coordinates -- Networks -- Trees -- Transactions -- Graphics of a Large Dataset. 
520 |a Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day? 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. Data visualization is useful for data cleaning, exploring data, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis and data mining. Data analysts, statisticians, computer scientists-indeed anyone who has to explore a large dataset of their own-should benefit from reading this book. 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. There are considerable advantages in extending displays which are well-known and well-tried, both in understanding how best to make use of them in your work and in presenting results to others. It should also make the book readily accessible for readers who already have a little experience of drawing statistical graphics. All ideas are illustrated with displays from analyses of real datasets and the authors emphasize the importance of interpreting displays effectively. Graphics should be drawn to convey information and the book includes many insightful examples. Antony Unwin holds the Chair of Computer Oriented Statistics and Data Analysis at the University of Augsburg. He has been involved in developing visualization software for twenty years. Martin Theus is a Senior Researcher at the University of Augsburg, has worked in industry and research in both Germany and the USA, and is the author of the visualization software Mondrian. Heike Hofmann is Assistant Professor of Statistics at Iowa State University. She wrote the software MANET and has also cooperated in the development of the GGobi software. 
650 0 |a Mathematics. 
650 0 |a Operations research. 
650 0 |a Decision making. 
650 0 |a Data mining. 
650 0 |a Computer graphics. 
650 0 |a Visualization. 
650 0 |a Computer software. 
650 0 |a Statistics. 
650 1 4 |a Mathematics. 
650 2 4 |a Mathematical Software. 
650 2 4 |a Statistical Theory and Methods. 
650 2 4 |a Visualization. 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Operation Research/Decision Theory. 
650 2 4 |a Computer Graphics. 
700 1 |a Theus, Martin.  |e author. 
700 1 |a Hofmann, Heike.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9780387329062 
830 0 |a Statistics and Computing,  |x 1431-8784 
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950 |a Mathematics and Statistics (Springer-11649)