000			03163nam a22003857a 4500
005			20250919005419.0
008			150818s20112011nyua b 001 0 eng d
020			_a9781441996497 _q(paperback) _cRM235.26
020			_a9781441996503 _q(paperback)
039		9	_a201602031122 _bbaiti _c201601280941 _dhamudah _y08-18-2015 _zhamudah
040			_aLTSCA _cLTSCA _dCDX _dYDXCP _dBWX _dDEBBG _dVRC _dUBY _dDLC _dUKM _erda
090			_aQA278.E9446
090			_aQA278 _b.E9446
100	1		_aEveritt, Brian. _eauthor.
245	1	3	_aAn introduction to applied multivariate analysis with R / _cBrian Everitt, Torsten Hothorn.
264		1	_aNew York : _bSpringer, _c2011.
264		4	_c©2011.
300			_axiv, 273 p. : _bill. ; _c24 cm.
490	1		_aUse R!
504			_aIncludes bibliographical references (p. 259-269) and index.
505	0		_aMultivariate data and multivariate analysis -- Looking at multivariate data: visualisation -- Principal components analysis -- Multidimensional scaling -- Exploratory factor analysis -- Cluster analysis -- Confirmatory factor analysis and structural equation models -- 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 _xData processing.
650		0	_aR (Computer program language)
700	1		_aHothorn, Torsten.
830		0	_aUse R!
907			_a.b16194524 _b2020-01-26 _c2019-11-12
942			_c01 _n0 _kQA278.E9446
914			_avtls003591877
990			_abety
991			_aFakulti Sains dan Teknologi
998			_at _b2015-05-08 _cm _da _feng _gnyu _y0 _z.b16194524
999			_c597199 _d597199