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001 287638
003 MX-SnUAN
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007 cr nn 008mamaa
008 150903s2011 xxu| o |||| 0|eng d
020 _a9781441996503
_99781441996503
024 7 _a10.1007/9781441996503
_2doi
035 _avtls000339381
039 9 _a201509030838
_bVLOAD
_c201404300359
_dVLOAD
_y201402060934
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aEveritt, Brian.
_eautor
_9303662
245 1 3 _aAn Introduction to Applied Multivariate Analysis with R /
_cby Brian Everitt, Torsten Hothorn.
264 1 _aNew York, NY :
_bSpringer New York,
_c2011.
300 _axiv, 274 páginas 92 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aUse R
500 _aSpringer eBooks
505 0 _aMultivariate data and multivariate analysis -- Looking at multivariate data: visualization -- Principal components analysis -- Multidimensional scaling.- Exploratory factor analysis -- Cluster analysis -- Confirmatory factor analysis and structural equation models -- The analysis of repeated measures data.-.
520 _aThe 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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aHothorn, Torsten.
_eautor
_9316921
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781441996497
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4419-9650-3
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c287638
_d287638