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008 110516s2011 njua ob 001 0 eng d
020 _a9781118018248
_q(electronic bk.)
020 _a1118018249
_q(electronic bk.)
020 _a9781118018262
020 _a1118018265
_q(E-Book)
020 _a9781118018255
_q(electronic bk.)
020 _a1118018257
_q(electronic bk.)
020 _a128310931X
020 _a9781283109314
020 _z9781118010648
_q(hardback)
020 _z1118010647
_q(hardback)
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049 _aMAIN
050 4 _aQA276.15
_b.H83 2011
072 7 _aMAT
_x029000
_2bisacsh
082 0 4 _a519.509
_222
084 _aMAT029000
_2bisacsh
100 1 _aHuber, Peter J.
245 1 0 _aData analysis : what can be learned from the past 50 years /
_cPeter J. Huber.
_h[electronic resource]
260 _aHoboken, N.J. :
_bWiley,
_c©2011.
300 _a1 online resource (xiv, 210 pages) :
_billustrations.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aWiley series in probability and statistics
504 _aIncludes bibliographical references and index.
505 0 _aWhat Is Data Analysis? -- Strategy Issues in Data Analysis -- Massive Data Sets -- Languages for Data Analysis -- Approximate Models -- Pitfalls -- Create Order in Data -- More Case Studies -- Wiley Series in Probability and Statistics.
520 _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.
520 _a"This book explores the many provocative questions concerning the fundamentals of data analysis"--
_cProvided by publisher.
588 0 _aPrint version record.
650 0 _aMathematical statistics
_xHistory.
650 0 _aMathematical statistics
_xPhilosophy.
650 0 _aNumerical analysis
_xMethodology.
650 4 _aMathematical statistics
_xHistory.
650 4 _aMathematical statistics
_xPhilosophy.
650 4 _aNumerical analysis
_xMethodology.
650 7 _aMATHEMATICS
_xProbability & Statistics
_xGeneral.
_2bisacsh
655 4 _aElectronic books.
655 0 _aElectronic books.
776 0 8 _iPrint version:
_aHuber, Peter J.
_tData analysis.
_dHoboken, N.J. : Wiley, ©2011
_z9781118010648
_w(DLC) 2010043284
_w(OCoLC)669751135
830 0 _aWiley series in probability and statistics.
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781118018255
_zWiley Online Library
942 _2ddc
_cBK
999 _c205057
_d205057