001452432 000__ 03674cam\a22005417i\4500
001452432 001__ 1452432
001452432 003__ OCoLC
001452432 005__ 20230310003355.0
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001452432 019__ $$a1365333795
001452432 020__ $$a9783031130052$$q(electronic bk.)
001452432 020__ $$a3031130057$$q(electronic bk.)
001452432 020__ $$z9783031130045
001452432 020__ $$z3031130049
001452432 0247_ $$a10.1007/978-3-031-13005-2$$2doi
001452432 035__ $$aSP(OCoLC)1366491396
001452432 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX
001452432 049__ $$aISEA
001452432 050_4 $$aQA278
001452432 08204 $$a519.53502855133$$223/eng/20230130
001452432 1001_ $$aZelterman, Daniel,$$eauthor.$$1https://isni.org/isni/0000000117208914
001452432 24510 $$aApplied multivariate statistics with R /$$cDaniel Zelterman.
001452432 250__ $$aSecond edition.
001452432 264_1 $$aCham :$$bSpringer,$$c2022.
001452432 300__ $$a1 online resource :$$billustrations (black and white, and colour).
001452432 336__ $$atext$$btxt$$2rdacontent
001452432 337__ $$acomputer$$bc$$2rdamedia
001452432 338__ $$aonline resource$$bcr$$2rdacarrier
001452432 4901_ $$aStatistics for biology and health
001452432 500__ $$aPrevious edition: 2015.
001452432 504__ $$aIncludes bibliographical references and index.
001452432 5050_ $$aChapter 1. Introduction -- Chapter 2. Elements of R -- Chapter 3. Graphical Displays -- Chapter 4. Basic Linear Algebra -- Chapter 5. The Univariate Normal Distribution -- Chapter 6. Bivariate Normal Distribution -- Chapter 7. Multivariate Normal Distribution -- Chapter 8. Factor Methods -- Chapter 9. Multivariate Linear Regression -- Chapter 10. Discrimination and Classification -- Chapter 11. Clustering Methods -- Chapter 12. Basic Models for Longitudinal Data -- Chapter 13. Time Series Models -- Chapter 14. Other Useful Methods.
001452432 506__ $$aAccess limited to authorized users.
001452432 520__ $$aNow in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.
001452432 588__ $$aDescription based on print version record.
001452432 650_0 $$aMultivariate analysis$$xData processing.
001452432 650_0 $$aR (Computer program language)
001452432 655_0 $$aElectronic books.
001452432 77608 $$iPrint version:$$aZelterman, Daniel.$$tApplied multivariate statistics with R.$$bSecond edition.$$dCham : Springer, 2022$$z9783031130045$$w(OCoLC)1346321564
001452432 830_0 $$aStatistics for biology and health.
001452432 852__ $$bebk
001452432 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-13005-2$$zOnline Access$$91397441.1
001452432 909CO $$ooai:library.usi.edu:1452432$$pGLOBAL_SET
001452432 980__ $$aBIB
001452432 980__ $$aEBOOK
001452432 982__ $$aEbook
001452432 983__ $$aOnline
001452432 994__ $$a92$$bISE