LEADER 03014nac# 2200397 i 450 001 VAN0036526 005 20240705120247.397 011 $a1431-8784 017 70$20$a21971706 100 $a20050524a1993 |0itac50 ba 102 $aDE 105 $a|||| ||||| 110 $ab|||||||||| 200 1 $aStatistics and computing 210 $aBerlin [etc.]$cSpringer$d1993- 463 1$1001VAN0123841$12001 $aApplied Quantitative Finance$fWolfgang Karl Härdle, Cathy Yi-Hsuan Chen, Ludger Overbeck editors$1205 $a3. ed$1210 $aBerlin$cSpringer$d2017$1215 $ax, 372 p.$cill.$d24 cm 463 1$1001VAN0278722$12001 $aApplied Statistical Learning$eWith Case Studies in Stata$fMatthias Schonlau$1210 $aCham$cSpringer$d2023$1215 $axv, 332 p.$cill.$d24 cm 463 1$1001VAN0276890$12001 $aApplied Time Series Analysis and Forecasting with Python$fChangquan Huang, Alla Petukhina$1210 $aCham$cSpringer$d2022$1215 $ax, 372 p.$cill.$d24 cm 463 1$1001VAN0123979$12001 $aBasic Elements of Computational Statistics$fWolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin$1210 $aCham$cSpringer$d2017$1215 $axxi, 305 p.$cill.$d24 cm 463 1$1001VAN0278813$12001 $aFundamentals of Supervised Machine Learning$eWith Applications in Python, R, and Stata$fGiovanni Cerulli$1210 $aCham$cSpringer$d2023$1215 $axxiv, 391 p.$cill.$d24 cm 463 1$1001VAN0124775$12001 $aIndependent Random Sampling Methods$fLuca Martino, David Luengo, Joaquín Míguez$1210 $aCham$cSpringer$d2018$1215 $axii, 280 p.$cill.$d24 cm 463 1$1001VAN0114408$12001 $aˆAn ‰introduction to statistics with Python$ewith applications in the life sciences$fThomas Haslwanter$1210 $a[Cham]$cSpringer$d2016$1215 $aXVII, 278 p.$cill.$d24 cm 463 1$1001VAN0276849$12001 $aˆAn ‰introduction to statistics with Python$ewith applications in the life sciences$fThomas Haslwanter$1205 $a2. ed$1210 $aCham$cSpringer$d2022$1215 $axvi, 336 p.$cill.$d24 cm 463 1$1001VAN0126972$12001 $aLinear Time Series with MATLAB and OCTAVE$fVíctor Gómez$1210 $aCham$cSpringer$d2019$1215 $axvii, 339 p.$cill.$d24 cm 463 1$1001VAN0115548$12001 $aS programming$fW. N. Venables, B. D. Ripley$1210 $aNew York$eetc.$cSpringer$d2000$1215 $aX, 264 p.$d24 cm. 463 1$1001VAN0279094$12001 $aVisualization and Imputation of Missing Values$eWith Applications in R$fMatthias Templ$1210 $aCham$cSpringer$d2023$1215 $axxii, 462 p.$cill.$d24 cm 463 1$1001VAN0036525$12001 $aModern applied statistics with S-PLUS$fW. N. Venables, B. D. Ripley$1210 $aNew York$cSpringer-Verlag$d1994$1215 $aXII, 462 p.$d24 cm$e1 floppy disk 517 1$3VAN0241934$aSCO 620 $aUS$dNew York$3VANL000011 620 $dBerlin$3VANL000066 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240712$gRICA 856 4 $uhttps://www.springer.com/series/3022$zhttps://www.springer.com/series/3022 912 $aVAN0036526 996 $aStatistics and computing$9786338 997 $aUNICAMPANIA