04099cam a22004817i 450000100090000000300040000900500170001300800410003001000170007101500190008801600180010702000150012502000350014003500240017504001950019904200140039405000250040808200290043310000290046224500910049125000190058226400360060126400110063730000460064833600260069433700280072033800270074850400670077550507970084252015500163965000310318965000410322065000420326165000280330365000340333165000370336565000480340265000470345065000230349765000360352065000310355665000300358720475111OSt20190702195030.0180427t20182018nyua b 001 0 eng a 2018942802 aGBB9084752bnb7 a0192095692Uk a0465094627 a9781541618411 (pbk.)cRs699.00 a(OCoLC)on1028523969 aBLRbengcYDXerdadBDXdTOHdOCOdORXdJRZdVP@dPAPdKCKdOCLCFdBURdUCWdB@LdPULdIC8dOCLCQdKZSdOCLCQdKLPdJPIdON3dHTMdIMDdHTMdUPMdIBAdOJ4dUKMGBdGZBdCHKdCHVBKdOCLCOdDLC alccopycat00aQA76.9.I52bP34 201804a001.4226 PAG223b0132971 aPage, Scott E.,eauthor.14aThe model thinker :bwhat you need to know to make data work for you /cScott E. Page. aFirst edition. 1aNew York :bBasic Books,c2018. 4c©2018 axiii, 427 pages :billustrations ;c24 cm atextbtxt2rdacontent aunmediatedbn2rdamedia avolumebnc2rdacarrier aIncludes bibliographical references (pages 357-409) and index.0 aThe many-model thinker -- Why model? -- The science of many models -- Modeling human actors -- Normal distributions : the bell curve -- Power-law distributions : long tails -- Linear models -- Concavity and convexity -- Models of value and power -- Network models -- Broadcast, diffusion, and contagion -- Entropy : modeling uncertainty -- Random walks -- Path dependence -- Local interaction models -- Lyapunov functions and equilibria -- Markov models -- Systems dynamics models -- Threshold models with feedbacks -- Spatial and hedonic choice -- Game theory models times three -- Models of cooperation -- Collective action problems -- Mechanism design -- Signaling models -- Models of learning -- Multi-armed bandit problems -- Rugged-landscape models -- Opioids, inequality, and humility. a"We confront no end of complex problems: why is inequality on the rise? Why are more and more Americans clinically obese? Does a racially diverse team make better decisions? How can we predict the outcomes of elections? At the same time, we find ourselves awash in data, be it on the opioid crisis, college admissions, genetic correlates of disease, financial transactions, or athletic performance. To confront such complexity and put that data to use, we need models: we can use linear regression to predict sales growth, or a power-law distribution to explain city sizes and book sales. Although each model offers insight, any single model will be wrong--just ask the physicist who, trying to understand barnyard animals, imagined a spherical cow. We must be able to do better. The question is simply how. In [this book], Scott E. Page gives us the answer: many-model thinking. By applying multiple diverse frameworks, we can achieve greater insights--indeed, using many models enables us to scale a hierarchy encompassing data, information, knowledge, and ultimately wisdom. Underpinning this, Page presents twenty-five broad classes of models--including models of growth, random walks, entropy, Markov chains, and many more--in a user-friendly and highly readable format, while teaching us how and when to apply them. Whether you work in science, business, government, or even literary studies, you confront complex problems, and you have more data than ever before. The Model Thinker will show how models can make that data work for you."-- 0aInformation visualization. 0aSocial systemsxMathematical models. 0aSocial sciencesxMathematical models. 0aComplexity (Philosophy) 7aComplexity (Philosophy)2fast 7aInformation visualization.2fast 7aSocial sciencesxMathematical models.2fast 7aSocial systemsxMathematical models.2fast 7aKomplexität2gnd 7aMathematische Modellierung2gnd 7aMathematisches Modell2gnd 7aSozialwissenschaften2gnd