LEADER 02437nam 2200589 450 001 9910823570303321 005 20231110213152.0 010 $a1-119-04364-6 010 $a1-119-03066-8 010 $a1-119-04357-3 010 $a1-119-04363-8 035 $a(CKB)4330000000001450 035 $a(DLC) 2015017261 035 $a(Au-PeEL)EBL1895958 035 $a(CaPaEBR)ebr11069584 035 $a(CaONFJC)MIL909280 035 $a(OCoLC)908287103 035 $a(Au-PeEL)EBL7104372 035 $a(JP-MeL)3000110644 035 $a(MiAaPQ)EBC1895958 035 $a(EXLCZ)994330000000001450 100 $a20150707h20162016 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cn$2rdamedia 183 $anc$2rdacarrier 200 10$aStatistical data analytics $efoundations for data mining, informatics, and knowledge discovery, $iSolutions manual /$fWalter W. Piegorsch 210 1$aChichester, England :$cWiley,$d2016. 210 4$d2016 215 $a1 online resource 225 0 $aSolutions Manual 311 $a1-118-61965-X 311 $a1-119-03065-X 320 $aIncludes bibliographical references. 327 $aCover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1 Data analytics and data mining -- Chapter 2 Basic probability and statistical distributions -- Chapter 3 Data manipulation -- Chapter 4 Data visualization and statistical graphics -- Chapter 5 Statistical inference -- Chapter 6 Techniques for supervised learning: simple linear regression -- Chapter 7 Techniques for supervised learning: multiple linear regression -- Chapter 8 Supervised learning: generalized linear models -- Chapter 9 Supervised learning: classification -- Chapter 10 Techniques for unsupervised learning: dimension reduction -- Chapter 11 Techniques for unsupervised learning: clustering and association -- References -- EULA. 410 0$aNew York Academy of Sciences 606 $aData mining$xMathematics 606 $aMathematical statistics 615 0$aData mining$xMathematics. 615 0$aMathematical statistics. 676 $a006.3/12 686 $a417$2njb/09 686 $a519.5$2njb/09 700 $aPiegorsch$b Walter W.$0292437 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910823570303321 996 $aStatistical data analytics$93963501 997 $aUNINA