02784cam a22003854a 450000100090000000300080000900500170001700800410003401000170007502000290009202000260012103500240014704000560017104200080022705000240023508200210025908400230028010000200030324500830032326000360040630000340044236500150047649000470049150400510053852012530058952001270184265000380196965000410200765000370204890600450208594200120213095500940214299900150223695201470225116497764BD-DhUL20140909111321.0101012s2011    njua     b    001 0 eng    a  2010043284  a9781118010648 (hardback)  a1118010647 (hardback)  a(OCoLC)ocn669751135  aDLCcDLCdYDXdBTCTAdYDXCPdBWXdCDXdDLCdBD-DhUL  apcc00aQA276.15b.H83 201100a519.509bHUD222  aMAT0290002bisacsh1 aHuber, Peter J.10aData analysis :bwhat can be learned from the past 50 years /cPeter J. Huber.  aHoboken, N.J. :bWiley,cc2011.  axiv, 210 p. :bill. ;c25 cm.  aUSDb98.960 aWiley series in probability and statistics  aIncludes bibliographical references and index.  a"This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniques is not of immediate value; rather, questions of strategy - when to use which technique - are employed. Central to the discussion is an understanding of the significance of massive (or robust) data sets, the implementation of languages, and the use of models. Each is sprinkled with an ample number of examples and case studies. Personal practices, various pitfalls, and existing controversies are presented when applicable. The book serves as an excellent philosophical and historical companion to any present-day text in data analysis, robust statistics, data mining, statistical learning, or computational statistics"--Provided by publisher.  a"This book explores the many provocative questions concerning the fundamentals of data analysis"--cProvided by publisher. 0aMathematical statisticsxHistory. 0aMathematical statisticsxPhilosophy. 0aNumerical analysisxMethodology.  a7bcbccorignewd1eecipf20gy-gencatlg  2ddccBK  bre04 2010-10-12cre04 2010-10-12 ONIX Scienceatc12 2011-06-09 1 copy rec'd., to CIP ver.  c9076d9076  00102ddc406519_509000000000000_HUD708NFIC916025aDUSLbDUSLcGENd2012-10-07ePurchasedo519.509 HUDp475625r2014-09-09w2014-09-09yBK