000			04155nam a22005895i 4500
001			978-0-387-37977-7
003			DE-He213
005			20161121231027.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387379777 _9978-0-387-37977-7
024	7		_a10.1007/0-387-37977-0 _2doi
050		4	_aQA76.75-76.765
072		7	_aUFM _2bicssc
072		7	_aCOM077000 _2bisacsh
082	0	4	_a004 _223
100	1		_aUnwin, Antony. _eauthor.
245	1	0	_aGraphics of Large Datasets _h[electronic resource] : _bVisualizing a Million / _cby Antony Unwin, Martin Theus, Heike Hofmann.
264		1	_aNew York, NY : _bSpringer New York, _c2006.
300			_aXIII, 271 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStatistics and Computing, _x1431-8784
505	0		_aBasics -- 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			_aGraphics 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	_aMathematics.
650		0	_aOperations research.
650		0	_aDecision making.
650		0	_aData mining.
650		0	_aComputer graphics.
650		0	_aVisualization.
650		0	_aComputer software.
650		0	_aStatistics.
650	1	4	_aMathematics.
650	2	4	_aMathematical Software.
650	2	4	_aStatistical Theory and Methods.
650	2	4	_aVisualization.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aOperation Research/Decision Theory.
650	2	4	_aComputer Graphics.
700	1		_aTheus, Martin. _eauthor.
700	1		_aHofmann, Heike. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387329062
830		0	_aStatistics and Computing, _x1431-8784
856	4	0	_uhttp://dx.doi.org/10.1007/0-387-37977-0
912			_aZDB-2-SMA
950			_aMathematics and Statistics (Springer-11649)
999			_c507497 _d507497