LEADER 04423nam 22007815 450 001 9910299761503321 005 20251116135407.0 010 $a3-319-14093-0 024 7 $a10.1007/978-3-319-14093-3 035 $a(CKB)3710000000460295 035 $a(EBL)3568013 035 $a(SSID)ssj0001546503 035 $a(PQKBManifestationID)16140872 035 $a(PQKBTitleCode)TC0001546503 035 $a(PQKBWorkID)14796231 035 $a(PQKB)11328684 035 $a(DE-He213)978-3-319-14093-3 035 $a(MiAaPQ)EBC3568013 035 $a(PPN)188461450 035 $a(EXLCZ)993710000000460295 100 $a20150803d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aApplied multivariate statistics with R /$fby Daniel Zelterman 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (401 p.) 225 1 $aStatistics for Biology and Health,$x1431-8776 300 $aDescription based upon print version of record. 311 08$a3-319-14092-2 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Elements of R -- Graphical Displays -- Basic Linear Algebra -- The Univariate Normal Distribution -- Bivariate Normal Distribution -- Multivariate Normal Distribution -- Factor Methods -- Multivariate Linear Regression -- Discrimination and Classification -- Clustering -- Time Series Models -- Other Useful Methods -- References -- Appendix -- Selected Solutions -- Index. 330 $aThis book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. . 410 0$aStatistics for Biology and Health,$x1431-8776 606 $aStatistics 606 $aBiometry 606 $aEpidemiology 606 $aBioinformatics 606 $aSystems biology 606 $aR (Computer program language) 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 606 $aBiostatistics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15020 606 $aEpidemiology$3https://scigraph.springernature.com/ontologies/product-market-codes/H63000 606 $aBioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15001 606 $aSystems Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/L15010 615 0$aStatistics. 615 0$aBiometry. 615 0$aEpidemiology. 615 0$aBioinformatics. 615 0$aSystems biology. 615 0$aR (Computer program language) 615 14$aStatistics for Life Sciences, Medicine, Health Sciences. 615 24$aBiostatistics. 615 24$aEpidemiology. 615 24$aBioinformatics. 615 24$aSystems Biology. 676 $a519.535 700 $aZelterman$b Daniel$4aut$4http://id.loc.gov/vocabulary/relators/aut$0144977 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299761503321 996 $aApplied multivariate statistics with R$91522551 997 $aUNINA