00000cmm a22000004a 4500 UP-99796217611212063 Buklod 20230215085534.0 m go j cr |nu|||auu|a 110422s2011 xxu u | eng d 9781441996503 (eBook) 1441996508 (eBook) (iLib)UPD-00214608219 DLC DML eng DMLUC QA 278 E87 2011eb Everitt, Brian An introduction to applied multivariate analysis with R [electronic resource] Brian Everitt, Torsten Hothorn. New York Springer c2011. 1 online resource (xiv, 273 p.) ill. Use R Multivariate 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. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. 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. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Multivariate analysis Data processing. R (Computer program language) Electronic books. Hothorn, Torsten. SpringerLink (Online service). Electronic Resource Available for University of the Philippines Diliman via SpringerLink. Click here to access http://link.springer.com/book/10.1007/978-1-4419-9650-3 FO Monograph UPD DMLR Electronic Resource