000			06552cam a2200721 i 4500
001			on1114272857
003			OCoLC
005			20220908100202.0
006			m o d
007			cr |||||||||||
008			190822s2020 nju ob 001 0 eng
010			_a 2019022972
040			_aDLC _beng _erda _cDLC _dOCLCF _dEBLCP _dTEFOD _dJSTOR _dUMI _dYDX _dN$T _dDEGRU _dWAU _dDLC _dOCLCO _dIEEEE _dRDF _dOCLCO
019			_a1139751049 _a1142202684
020			_a9780691198859 _q(ebook)
020			_a0691198853 _q(ebook)
020			_z9780691182377 _q(hardback)
020			_z069118237X _q(hardback)
035			_a(OCoLC)1114272857 _z(OCoLC)1139751049 _z(OCoLC)1142202684
037			_aA71EDE2B-1433-4466-8FB7-B4F72961F41F _bOverDrive, Inc. _nhttp://www.overdrive.com
037			_a22573/ctvmms98p _bJSTOR
037			_a9452425 _bIEEE
042			_apcc
050	0	0	_aQA276
072		7	_aCOM _x021030 _2bisacsh
072		7	_aCOM _x021000 _2bisacsh
072		7	_aCOM _x021040 _2bisacsh
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082	0	0	_a519.5 _223
084			_aSK 850 _qDE-16 _2rvk
049			_aMAIN
100	1		_aHand, D. J. _q(David J.), _d1950- _eauthor. _965402
245	1	0	_aDark data : _bwhy what you don't know matters / _cDavid J. Hand.
264		1	_aPrinceton : _bPrinceton University Press, _c[2020]
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bn _2rdamedia
338			_aonline resource _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"Data describe and represent the world. However, no matter how big they may be, data sets don't - indeed cannot - capture everything. Data are measurements - and, as such, they represent only what has been measured. They don't necessarily capture all the information that is relevant to the questions we may want to ask. If we do not take into account what may be missing/unknown in the data we have, we may find ourselves unwittingly asking questions that our data cannot actually address, come to mistaken conclusions, and make disastrous decisions. In this book, David Hand looks at the ubiquitous phenomenon of "missing data." He calls this "dark data" (making a comparison to "dark matter" - i.e., matter in the universe that we know is there, but which is invisible to direct measurement). He reveals how we can detect when data is missing, the types of settings in which missing data are likely to be found, and what to do about it. It can arise for many reasons, which themselves may not be obvious - for example, asymmetric information in wars; time delays in financial trading; dropouts in clinical trials; deliberate selection to enhance apparent performance in hospitals, policing, and schools; etc. What becomes clear is that measuring and collecting more and more data (big data) will not necessarily lead us to better understanding or to better decisions. We need to be vigilant to what is missing or unknown in our data, so that we can try to control for it. How do we do that? We can be alert to the causes of dark data, design better data-collection strategies that sidestep some of these causes - and, we can ask better questions of our data, which will lead us to deeper insights and better decisions"-- _cProvided by publisher.
588			_aDescription based on print version record and CIP data provided by publisher.
505	0		_aPreface; Part 1: Dark Data: Their Origins and Consequences; Chapter 1: Dark Data: What We Don't See Shapes Our World; The Ghost of Data; So You Think You Have All the Data?; Nothing Happened, So We Ignored It; The Power of Dark Data; All around Us; Chapter 2: Discovering Dark Data: What We Collect and What We Don't; Dark Data on All Sides; Data Exhaust, Selection, and Self-Selection; From the Few to the Many; Experimental Data; Beware Human Frailties; Chapter 3: Definitions and Dark Data: What Do You Want to Know?; Different Definitions and Measuring the Wrong Thing
505	8		_aYou Can't Measure EverythingScreening; Selection on the Basis of Past Performance; Chapter 4: Unintentional Dark Data: Saying One Thing, Doing Another; The Big Picture; Summarizing; Human Error; Instrument Limitations; Linking Data Sets; Chapter 5: Strategic Dark Data: Gaming, Feedback, and Information Asymmetry; Gaming; Feedback; Information Asymmetry; Adverse Selection and Algorithms; Chapter 6: Intentional Dark Data: Fraud and Deception; Fraud; Identity Theft and Internet Fraud; Personal Financial Fraud; Financial Market Fraud and Insider Trading; Insurance Fraud; And More
505	8		_aChapter 7: Science and Dark Data: The Nature of DiscoveryThe Nature of Science; If Only I'd Known That; Tripping over Dark Data; Dark Data and the Big Picture; Hiding the Facts; Retraction; Provenance and Trustworthiness: Who Told You That?; Part II: Illuminating and Using Dark Data; Chapter 8: Dealing with Dark Data: Shining a Light; Hope!; Linking Observed and Missing Data; Identifying the Missing Data Mechanism; Working with the Data We Have; Going Beyond the Data: What If You Die First?; Going Beyond the Data: Imputation; Iteration; Wrong Number!
505	8		_aChapter 9: Benefiting from Dark Data: Reframing the QuestionHiding Data; Hiding Data from Ourselves: Randomized Controlled Trials; What Might Have Been; Replicated Data; Imaginary Data: The Bayesian Prior; Privacy and Confidentiality Preservation; Collecting Data in the Dark; Chapter 10: Classifying Dark Data: A Route through the Maze; A Taxonomy of Dark Data; Illumination; Notes; Index.
590			_aIEEE _bIEEE Xplore Princeton University Press eBooks Library
650		0	_aMissing observations (Statistics) _965403
650		0	_aBig data. _94174
650		6	_aObservations manquantes (Statistique) _965404
650		6	_aDonn�ees volumineuses. _965405
650		7	_aCOMPUTERS _xDatabase Management _xData Mining. _2bisacsh _96841
650		7	_aBig data. _2fast _0(OCoLC)fst01892965 _94174
650		7	_aMissing observations (Statistics) _2fast _0(OCoLC)fst01023700 _965403
655		4	_aElectronic books. _93294
776	0	8	_iPrint version: _aHand, D. J. (David J.), 1950- _tDark data _dPrinceton : Princeton University Press, [2020] _z9780691182377 _w(DLC) 2019022971
856	4	0	_uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=9452425
938			_aYBP Library Services _bYANK _n16358388
938			_aEBSCOhost _bEBSC _n2218633
938			_aProQuest Ebook Central _bEBLB _nEBL5981613
938			_aDe Gruyter _bDEGR _n9780691198859
942			_cEBK
994			_a92 _bINTKS
999			_c81454 _d81454