000			02157cam a22002654a 4500
008			101012s2011 njua b 001 0 eng
020			_a9781118010648
020			_a1118010647
040			_aSDU
050	0	0	_aQA276 _bH877 D 2011
100	1		_aHuber, Peter J. _9193270
245	1	0	_aData analysis : _bwhat can be learned from the past 50 years / _cPeter J. Huber.
260			_aHoboken, N.J. : _bWiley, _c2011.
300			_a210 p. : _bill.
490	0		_aWiley series in probability and statistics
505			_aHKBU library
518			_aYT2025 M10
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"--
650		0	_aMathematical statistics _xHistory. _9193271
650		0	_aMathematical statistics _xPhilosophy. _9193272
650		0	_aNumerical analysis _xMethodology. _9193273
900			_a= C.1 SDU
942			_cGBE _2lcc
999			_c104010 _d104010