MARC Record from marc_columbia

LEADER: 06279cam a2200721Ii 4500
001 15076036
005 20220326231333.0
006 m o d
007 cr mn|||||||||
008 090601t20092009flua ob 001 0 eng d
035 $a(OCoLC)ocn367646520
035 $a(NNC)15076036
040 $aN$T$beng$erda$epn$cN$T$dOCLCQ$dE7B$dOCLCQ$dOHS$dEBLCP$dOCLCQ$dDEBSZ$dYDXCP$dMHW$dWAU$dOCLCQ$dOCLCO$dOCLCF$dOCLCQ$dNLE$dMERUC$dOCLCO$dUUM$dOCLCQ$dAU@$dOCLCO$dOCLCQ$dUKMGB$dOCLCO$dOCLCA$dYDX$dOCLCQ$dK6U$dOCLCO$dOSU$dOCLCO
015 $aGBB7A9600$2bnb
016 7 $a018392200$2Uk
019 $a646806994$a712982369$a785720697$a992558410$a1058391894$a1058775869$a1096697049
020 $a9781420010152$q(electronic bk.)
020 $a1420010158$q(electronic bk.)
020 $z9781584883340
020 $z1584883340
035 $a(OCoLC)367646520$z(OCoLC)646806994$z(OCoLC)712982369$z(OCoLC)785720697$z(OCoLC)992558410$z(OCoLC)1058391894$z(OCoLC)1058775869$z(OCoLC)1096697049
037 $aTANDF_184155$bIngram Content Group
050 4 $aQA279$b.M48eb vol. 1
060 4 $aQA 279
072 7 $aMAT$x029000$2bisacsh
082 04 $a519.5/38$222
049 $aZCUA
100 1 $aMilliken, George A.,$d1943-$eauthor.
245 10 $aAnalysis of messy data.$nVolume 1,$pDesigned experiments /$cGeorge A. Milliken, Dallas E. Johnson.
246 30 $aDesigned experiments
250 $aSecond ed.
264 1 $aBoca Raton :$bCRC Press,$c[2009]
264 4 $c©2009
300 $a1 online resource (xiii, 674 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aAnalysis of Messy Data ;$vv. 1
500 $a"A Chapman & Hall book."
520 $a"A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since the original publication. New to the Second Edition Several modern suggestions for multiple comparison procedures Additional examples of split-plot designs and repeated measures designs The use of SAS-GLM to analyze an effects model The use of SAS-MIXED to analyze data in random effects experiments, mixed model experiments, and repeated measures experiments The book explores various techniques for multiple comparison procedures, random effects models, mixed models, split-plot experiments, and repeated measures designs. The authors implement the techniques using several statistical software packages and emphasize the distinction between design structure and the structure of treatments. They introduce each topic with examples, follow up with a theoretical discussion, and conclude with a case study. Bringing a classic work up to date, this edition will continue to show readers how to effectively analyze real-world, nonstandard data sets"--Provided by publisher.
504 $aIncludes bibliographical references and index.
505 0 $aThe simplest case: one-way treatment structure in a completely randomized design structure with homogeneous errors -- One-way treatment structure in a completely randomized design structure with heterogeneous errors -- Simultaneous inference procedures and multiple comparisons -- Basics for designing experiments -- Multilevel designs: split-plots, strip-plots, repeated measures and combinations -- Matrix form of the model -- Balanced two-way treatment structures -- Case study: complete analyses of balanced two-way experiments -- Using the means model to analyze balanced two-way treatment structures with unequal subclass numbers -- Using the effects model to analyze balanced two-way treatment structures with unequal subclass numbers -- Analyzing large balanced two-way experiments having unequal subclass numbers -- Case study: balanced two-way treatment structure with unequal subclass numbers -- Using the means model to analyze two-way treatment structures with missing treatment combinations -- Using the effects model to analyze two-way treatment structures with missing treatment combinations -- Case study: two-way treatment structure with missing treatment combinations -- Analyzing three-way and higher-order treatment structures -- Case study: three-way treatment structure with many missing treatment combinations -- Random effects models and variance components -- Methods for estimating variance components -- Methods for making inferences about variance components -- Case study: analysis of a random effects model -- Analysis of mixed models -- Case studies of a mixed Model -- Methods for analyzing split-plot type designs -- Methods for analyzing strip-plot type designs -- Methods for analyzing repeated measures experiments -- Analysis of repeated measures experiments when the ideal conditions are not satisfied -- Case studies: complex examples having repeated measures -- Analysis of crossover designs -- Analysis of nested designs
588 $aDescription based on print version record
650 0 $aAnalysis of variance.
650 0 $aExperimental design.
650 0 $aSampling (Statistics)
650 2 $aAnalysis of Variance
650 2 $aResearch Design
650 2 $aSampling Studies
650 6 $aAnalyse de variance.
650 6 $aPlan d'expérience.
650 6 $aÉchantillonnage (Statistique)
650 7 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 7 $aAnalysis of variance.$2fast$0(OCoLC)fst00808330
650 7 $aExperimental design.$2fast$0(OCoLC)fst00918404
650 7 $aSampling (Statistics)$2fast$0(OCoLC)fst01104676
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aJohnson, Dallas E.,$d1938-
776 08 $iPrint version:$aMilliken, George A., 1943-$tAnalysis of messy data. Volume 1, Designed experiments.$b2nd ed.$dBoca Raton : CRC Press, ©2009$z9781584883340$z1584883340$w(DLC) 2008045111$w(OCoLC)263065413
830 0 $aAnalysis of Messy Data.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15076036$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS