LEADER 01894oam 2200613zu 450 001 996199770203316 005 20230323184024.0 035 $a(CKB)1000000000021847 035 $a(SSID)ssj0000393630 035 $a(PQKBManifestationID)12151860 035 $a(PQKBTitleCode)TC0000393630 035 $a(PQKBWorkID)10372910 035 $a(PQKB)10796229 035 $a(EXLCZ)991000000000021847 100 $a20160829d2004 uy 101 0 $aeng 181 $ctxt 182 $cc 183 $acr 200 10$aBIBE 2004 : proceedings : 19-21 May, 2004, Taichung, Taiwan, ROC 210 31$a[Place of publication not identified]$cIEEE Computer Society$d2004 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-7695-2173-8 606 $aBiomedical Engineering 606 $aComputational Biology 606 $aMedical Informatics 606 $aBiology 606 $aHealth Occupations 606 $aEngineering 606 $aInformation Science 606 $aInformatics 606 $aBiological Science Disciplines 606 $aTechnology, Industry, and Agriculture 606 $aOccupations 606 $aNatural Science Disciplines 615 2$aBiomedical Engineering 615 2$aComputational Biology 615 2$aMedical Informatics 615 2$aBiology 615 2$aHealth Occupations 615 2$aEngineering 615 2$aInformation Science 615 2$aInformatics 615 2$aBiological Science Disciplines 615 2$aTechnology, Industry, and Agriculture 615 2$aOccupations 615 2$aNatural Science Disciplines 712 02$aIEEE Neural Networks Society 712 02$aIEEE Computer Society 801 0$bPQKB 906 $aPROCEEDING 912 $a996199770203316 996 $aBIBE 2004 : proceedings : 19-21 May, 2004, Taichung, Taiwan, ROC$92341847 997 $aUNISA LEADER 04866oam 2200901 450 001 9910554499403321 005 20240102235722.0 010 $a0-231-55335-8 024 7 $a10.7312/clay19994 035 $a(OCoLC)1240264669 035 $a(OCoLC)on1240264669 035 $a(DE-B1597)600423 035 $a(DE-B1597)9780231553353 035 $a(MiAaPQ)EBC6381596 035 $a(PPN)266300812 035 $a(CKB)4100000011991954 035 $a(EXLCZ)994100000011991954 100 $a20210226d2021 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBernoulli's fallacy $estatistical illogic and the crisis of modern science /$fAubrey Clayton 210 1$aNew York :$cColumbia University Press,$d[2021] 215 $a1 online resource (xviii, 347 pages) $cillustrations 311 08$aPrint version: Clayton, Aubrey. Bernoulli's fallacy New York : Columbia University Press, 2021. 9780231199940 (DLC) 2021004250 320 $aIncludes bibliographical references and index. 327 $tIntroduction --$t1. What is probability? --$t2. The titular fallacy --$t3. Adolphe quetelet's bell curve bridge --$t4. The frequentist jihad --$t5. The quote-unquote logic of orthodox statistics --$t6. The replication crisis/opportunity --$t7. The way out. 330 $a"There is a logical flaw in the statistical methods used across experimental science. This fault is not just a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly data-reliant culture, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences. The foundation of the problem is a misunderstanding of probability and our ability to make inferences from data. Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. He recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. Clayton highlights how influential nineteenth- and twentieth-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics. Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach-incorporating prior knowledge when reasoning with incomplete information-in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli's Fallacy explains why something has gone wrong with how we use data-and how to fix it"--$cProvided by publisher. 606 $aProbabilities$xPhilosophy$y19th century 606 $aProbabilities$xPhilosophy$y20th century 606 $aMathematical statistics$xPhilosophy 606 $aBinomial distribution 606 $aLaw of large numbers 606 $aMATHEMATICS / History & Philosophy$2bisacsh 606 $aBinomial distribution$2fast$3(OCoLC)fst00831915 606 $aInfluence (Literary, artistic, etc.)$2fast$3(OCoLC)fst00972484 606 $aLaw of large numbers$2fast$3(OCoLC)fst00994048 606 $aMathematical statistics$xPhilosophy$2fast$3(OCoLC)fst01012143 606 $aProbabilities$xPhilosophy$2fast$3(OCoLC)fst01077746 610 $aBayesian statistics. 610 $afrequentist statistics. 610 $ahistory of math. 610 $ahistory of statistics. 610 $aprobability. 610 $areplication crisis. 610 $astatistics and science. 610 $astatistics. 615 0$aProbabilities$xPhilosophy 615 0$aProbabilities$xPhilosophy 615 0$aMathematical statistics$xPhilosophy. 615 0$aBinomial distribution. 615 0$aLaw of large numbers. 615 7$aMATHEMATICS / History & Philosophy 615 7$aBinomial distribution. 615 7$aInfluence (Literary, artistic, etc.) 615 7$aLaw of large numbers. 615 7$aMathematical statistics$xPhilosophy. 615 7$aProbabilities$xPhilosophy. 676 $a519.2 700 $aClayton$b Aubrey$01218357 801 0$bDLC 801 1$bDLC 801 2$bOCLCO 801 2$bOCLCF 801 2$bEBLCP 801 2$bN$T 801 2$bUKAHL 801 2$bYDX 801 2$bJSTOR 801 2$bDEGRU 801 2$bUCW 801 2$bTEFOD 906 $aBOOK 912 $a9910554499403321 996 $aBernoulli's fallacy$92817477 997 $aUNINA LEADER 04270nam 22006735 450 001 9910357843603321 005 20251116220651.0 010 $a3-030-28444-1 024 7 $a10.1007/978-3-030-28444-2 035 $a(CKB)4100000009938028 035 $a(MiAaPQ)EBC5983967 035 $a(DE-He213)978-3-030-28444-2 035 $a(PPN)250193183 035 $a(EXLCZ)994100000009938028 100 $a20191123d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Visualisation with R $e111 Examples /$fby Thomas Rahlf 205 $a2nd ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (461 pages) 311 08$a3-030-28443-3 327 $aData for Everybody -- Structure and Technical Requirements -- Implementation in R -- Beyond R -- Regarding the Examples -- Categorical Data -- Distributions -- Time Series -- Scatter Plots -- Maps -- Illustrative Examples -- Interactive Visualisation with JavaScript: Highcharts and Mapael -- Appendix. 330 $aThis book introduces readers to the fundamentals of creating presentation graphics using R, based on 111 detailed and complete scripts. It shows how bar and column charts, population pyramids, Lorenz curves, box plots, scatter plots, time series, radial polygons, Gantt charts, heat maps, bump charts, mosaic and balloon charts, and a series of different thematic map types can be created using R?s Base Graphics System. Every example uses real data and includes step-by-step explanations of the figures and their programming. This second edition contains additional examples for cartograms, chord-diagrams and networks, and interactive visualizations with Javascript. The open source software R is an established standard and a powerful tool for various visualizing applications, integrating nearly all technologies relevant for data visualization. The basic software, enhanced by more than 14000 extension packs currently freely available, is intensively used by organizations including Google, Facebook and the CIA. The book serves as a comprehensive reference guide to a broad variety of applications in various fields. This book is intended for all kinds of R users, ranging from experts, for whom especially the example codes are particularly useful, to beginners, who will find the finished graphics most helpful in learning what R can actually deliver. Features and Benefits Offers a comprehensive introduction to creating presentation graphics with R Presents the complete code of 111 examples from various fields Includes step-by-step explanations of the programming of figures, based on real data. 606 $aComputer graphics 606 $aStatistics 606 $aApplication software 606 $aComputer software 606 $aR (Computer program language) 606 $aVisualització de la informació$2thub 606 $aR (Llenguatge de programació)$2thub 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 606 $aStatistics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/S0000X 606 $aComputer Applications$3https://scigraph.springernature.com/ontologies/product-market-codes/I23001 606 $aProfessional Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I29000 608 $aLlibres electrònics$2thub 615 0$aComputer graphics. 615 0$aStatistics. 615 0$aApplication software. 615 0$aComputer software. 615 0$aR (Computer program language) 615 7$aVisualització de la informació. 615 7$aR (Llenguatge de programació) 615 14$aComputer Graphics. 615 24$aStatistics, general. 615 24$aComputer Applications. 615 24$aProfessional Computing. 676 $a001.4226 700 $aRahlf$b Thomas$4aut$4http://id.loc.gov/vocabulary/relators/aut$01059737 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910357843603321 996 $aData Visualisation with R$92508007 997 $aUNINA