000			03369nam a22004577a 4500
999			_c34010 _d34010
003			CUTN
005			20201221124708.0
008			201221b ||||| |||| 00| 0 eng d
020			_a9781441996497
020			_a9781441996494
020			_a9781441996503
041			_aEnglish
082	0	4	_a519.535 _222 _bEVE
100	1		_aEveritt, Brian.
245	1	3	_aAn introduction to applied multivariate analysis with R / _cBrian Everitt, Torsten Hothorn.
260			_aNew York : _bSpringer, _cc2011.
300			_axiv, 273 p. : _bill. ; _c24 cm.
505	0		_a _t1. Multivariate data and multivariate analysis -- _t2. Looking at multivariate data: visualisation -- _t3. Principal components analysis -- _t4. Multidimensional scaling -- _t5. Exploratory factor analysis -- _t6. Cluster analysis -- _t7. Confirmatory factor analysis and structural equation models -- _t8. The analysis of repeated measures data.
520			_a"The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data."--Publisher's description.
650		0	_aMultivariate analysis
650		0	_aR (Computer program language)
650	0	7	_aMultivariate Analyse.
650	0	7	_aR (Programm)
700	1		_aHothorn, Torsten.
856	4	2	_uhttp://www.loc.gov/catdir/enhancements/fy1304/2011926793-b.html
856	4	2	_uhttp://www.loc.gov/catdir/enhancements/fy1304/2011926793-d.html
856	4	1	_uhttp://www.loc.gov/catdir/enhancements/fy1304/2011926793-t.html
942			_2ddc _cBOOKS
490	1		_aUse R!
504			_aIncludes bibliographical references (p. 259-269) and index.
650		0	_xData processing.
650	0	7	_2swd
650	0	7	_2swd
830		0	_aUse R!
856	4	2	_3Contributor biographical information
856	4	2	_3Publisher description
856	4	1	_3Table of contents only
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg