LEADER 01368nam2-2200433---450- 001 990000829500203316 005 20051219115749.0 010 $a88-02-04342-6 035 $a0082950 035 $aUSA010082950 035 $a(ALEPH)000082950USA01 035 $a0082950 100 $a20020102d1991----km-y1itay0103----ba 101 $aita 102 $aIT 105 $aa|||||||001yy 200 1 $a<<4.>> : <> chiusure orizzontali$ele c.o. piane inclinate, le c.o. curve$fEnrico Mandolesi 210 $aTorino$cUTET$dcopyr. 1991 215 $aXVIII, 473 p.$cill.$d29 cm 461 1$10010082886$12001$aEdilizia 606 0 $aEdifici$xCostruzione 676 $a690 700 1$aMANDOLESI,$bEnrico$01278 801 0$aIT$bUNFI$c19990422 912 $a990000829500203316 951 $a690 MAN 4$b16667 Ing.$c690$d00079709 951 $a690 MAN 4$b19351 Ing.$c690$d00180800 951 $a690 MAN 4$b19352 Ing.$c690$d00180795 959 $aBK 969 $aTEC 979 $aJOHNNY$b90$c20020102$lUSA01$h1358 979 $aJOHNNY$b90$c20020102$lUSA01$h1401 979 $c20020403$lUSA01$h1728 979 $aPATRY$b90$c20040406$lUSA01$h1657 979 $aPECORARO$b90$c20051219$lUSA01$h1121 979 $aPECORARO$b90$c20051219$lUSA01$h1124 979 $aPECORARO$b90$c20051219$lUSA01$h1157 996 $aChiusure orizzontali$9967334 997 $aUNISA LEADER 01307nam 2200421 450 001 9910467849603321 005 20200520144314.0 035 $a(CKB)4100000009151272 035 $a(MiAaPQ)EBC5881931 035 $a(Au-PeEL)EBL5881931 035 $a(OCoLC)1114968135 035 $a(EXLCZ)994100000009151272 100 $a20190926d2017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a180 days of problem solving for sixth grade /$fauthor, Stacy Monsman 210 1$aHuntington Beach, California :$cShell Education,$d[2017] 210 4$dİ2017 215 $a1 online resource (232 pages) $cillustrations 225 1 $aPractice-assess-diagnose 311 $a1-4258-1618-5 311 $a1-4258-9582-4 410 0$aPractice-assess-diagnose. 606 $aMathematics$xStudy and teaching (Middle school)$zUnited States 608 $aElectronic books. 615 0$aMathematics$xStudy and teaching (Middle school) 676 $a510.71273 700 $aMonsman$b Stacy$0945591 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910467849603321 996 $a180 days of problem solving for sixth grade$92149779 997 $aUNINA LEADER 05049nam 22005775 450 001 9910300104803321 005 20251116195412.0 010 $a3-319-71404-X 024 7 $a10.1007/978-3-319-71404-2 035 $a(CKB)4100000002892129 035 $a(MiAaPQ)EBC5347221 035 $a(DE-He213)978-3-319-71404-2 035 $a(PPN)225551217 035 $a(EXLCZ)994100000002892129 100 $a20180319d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNumerical Ecology with R /$fby Daniel Borcard, François Gillet, Pierre Legendre 205 $a2nd ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (xv, 435 pages) $cillustrations 225 1 $aUse R!,$x2197-5736 311 08$a3-319-71403-1 327 $aChapter 1. Introduction -- Chapter 2. Exploratory Data Analysis -- Chapter 3. Association Measures and Matrices -- Chapter 4. Cluster Analysis -- Chapter 5. Unconstrained Ordination -- Chapter 6. Canonical Ordination -- Chapter 7. Spatial Analysis of Ecological Data -- Chapter 8. Community Diversity. 330 $aThis new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis. This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/). 410 0$aUse R!,$x2197-5736 606 $aStatistics 606 $aEcology 606 $aEnvironmental sciences 606 $aR (Computer program language) 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aTheoretical Ecology/Statistics$3https://scigraph.springernature.com/ontologies/product-market-codes/L19147 606 $aMath. Appl. in Environmental Science$3https://scigraph.springernature.com/ontologies/product-market-codes/U24005 615 0$aStatistics. 615 0$aEcology. 615 0$aEnvironmental sciences. 615 0$aR (Computer program language) 615 14$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aTheoretical Ecology/Statistics. 615 24$aMath. 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