LEADER 03804nam 22005535 450 001 9910300119303321 005 20200702230332.0 010 $a3-319-64583-8 024 7 $a10.1007/978-3-319-64583-4 035 $a(CKB)4340000000223308 035 $a(DE-He213)978-3-319-64583-4 035 $a(MiAaPQ)EBC6315441 035 $a(MiAaPQ)EBC5579313 035 $a(Au-PeEL)EBL5579313 035 $a(OCoLC)1066195566 035 $z(PPN)258872705 035 $a(PPN)221254536 035 $a(EXLCZ)994340000000223308 100 $a20171129d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExperimental Design$b[electronic resource] $eWith Application in Management, Engineering, and the Sciences. /$fby Paul D. Berger, Robert E. Maurer, Giovana B. Celli 205 $a2nd ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XVIII, 639 p. 159 illus., 150 illus. in color.) 300 $aIncludes index. 311 $a3-319-64582-X 327 $a1. Introduction to experimental design -- 2. One-factor designs and the analysis of variance -- 3. Some further considerations on one-factor design and ANOVA -- 4. Multiple-comparison testing -- 5. Orthogonality, orthogonal decomposition, and their role in modern experimental design -- 6 -- Two-factor cross-classification designs -- 7. Nested, or hierarchical, designs -- 8. Designs with three or more factors: Latin-square and related designs -- 9. Two-level factorial designs -- 10. Confounding/blocking in 2k designs -- 11. Two-level fractional-factorial designs -- 12. Designs with factors at three levels -- 13. Introduction to Taguchi methods -- 14. Simple regression -- 15. Multiple and step-wise regression -- 16. Introduction to Response-Surface Methodology -- 17. Introduction to mixture design and triangular surfaces -- 18. Literature on experimental design and discussion. 330 $aThis text introduces and provides instruction on the design and analysis of experiments for a broad audience. Formed by decades of teaching, consulting, and industrial experience in the Design of Experiments field, this new edition contains updated examples, exercises, and situations covering the science and engineering practice. This text minimizes the amount of mathematical detail, while still doing full justice to the mathematical rigor of the presentation and the precision of statements, making the text accessible for those who have little experience with design of experiments and who need some practical advice on using such designs to solve day-to-day problems. Additionally, an intuitive understanding of the principles is always emphasized, with helpful hints throughout. 606 $aStatistics  606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 615 0$aStatistics . 615 14$aStatistical Theory and Methods. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 676 $a519.57 700 $aBerger$b Paul D$4aut$4http://id.loc.gov/vocabulary/relators/aut$0594156 702 $aMaurer$b Robert E$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aCelli$b Giovana B$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910300119303321 996 $aExperimental Design$92050575 997 $aUNINA