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001440080 001__ 1440080
001440080 003__ OCoLC
001440080 005__ 20230309004540.0
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001440080 019__ $$a1273077593$$a1273122896$$a1287770936
001440080 020__ $$a9783030698270$$q(electronic bk.)
001440080 020__ $$a3030698270$$q(electronic bk.)
001440080 020__ $$z3030698262
001440080 020__ $$z9783030698263
001440080 0247_ $$a10.1007/978-3-030-69827-0$$2doi
001440080 035__ $$aSP(OCoLC)1272957381
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001440080 049__ $$aISEA
001440080 050_4 $$aQA276
001440080 08204 $$a519.5$$223
001440080 1001_ $$aKauermann, Göran,$$eauthor.
001440080 24510 $$aStatistical foundations, reasoning and inference :$$bfor science and data science /$$cGöran Kauermann, Helmut Küchenhoff, Christian Heumann.
001440080 260__ $$aCham, Switzerland :$$bSpringer,$$c2021.
001440080 300__ $$a1 online resource
001440080 336__ $$atext$$btxt$$2rdacontent
001440080 337__ $$acomputer$$bc$$2rdamedia
001440080 338__ $$aonline resource$$bcr$$2rdacarrier
001440080 347__ $$atext file
001440080 347__ $$bPDF
001440080 4901_ $$aSpringer series in statistics,$$x2197-568X
001440080 504__ $$aIncludes bibliographical references and index.
001440080 5050_ $$aIntroduction -- Background in Probability -- Parametric Statistical Models -- Maximum Likelihood Inference -- Bayesian Statistics -- Statistical Decisions -- Regression -- Bootstrapping -- Model Selection and Model Averaging -- Multivariate and Extreme Value Distributions -- Missing and Deficient Data -- Experiments and Causality.
001440080 506__ $$aAccess limited to authorized users.
001440080 520__ $$aThis textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master' students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.
001440080 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 5, 2021).
001440080 650_0 $$aMathematical statistics.
001440080 655_7 $$aLlibres electrònics.$$2thub
001440080 655_0 $$aElectronic books.
001440080 7001_ $$aKüchenhoff, Helmut,$$eauthor.
001440080 7001_ $$aHeumann, Christian,$$d1962-$$eauthor.
001440080 77608 $$iPrint version:$$z3030698262$$z9783030698263$$w(OCoLC)1232272773
001440080 830_0 $$aSpringer series in statistics,$$x2197-568X
001440080 852__ $$bebk
001440080 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-69827-0$$zOnline Access$$91397441.1
001440080 909CO $$ooai:library.usi.edu:1440080$$pGLOBAL_SET
001440080 980__ $$aBIB
001440080 980__ $$aEBOOK
001440080 982__ $$aEbook
001440080 983__ $$aOnline
001440080 994__ $$a92$$bISE