001435863 000__ 04408cam\a2200553\i\4500
001435863 001__ 1435863
001435863 003__ OCoLC
001435863 005__ 20230309003956.0
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001435863 008__ 210418s2021\\\\sz\\\\\\ob\\\\001\0\eng\d
001435863 019__ $$a1284935781
001435863 020__ $$a9783030696412$$q(electronic bk.)
001435863 020__ $$a3030696413$$q(electronic bk.)
001435863 020__ $$z9783030696405
001435863 020__ $$z3030696405
001435863 0247_ $$a10.1007/978-3-030-69641-2$$2doi
001435863 035__ $$aSP(OCoLC)1246445644
001435863 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dOCLCO$$dEBLCP$$dOCLCF$$dUKAHL$$dOCLCQ$$dOCLCO$$dCOM$$dN$T$$dSFB$$dOCLCQ
001435863 049__ $$aISEA
001435863 050_4 $$aQH316.5
001435863 08204 $$a570.72/7$$223
001435863 1001_ $$aKaltenbach, Hans-Michael,$$eauthor.
001435863 24510 $$aStatistical design and analysis of biological experiments /$$cHans-Michael Kaltenbach.
001435863 264_1 $$aCham :$$bSpringer,$$c[2021]
001435863 300__ $$a1 online resource
001435863 336__ $$atext$$btxt$$2rdacontent
001435863 337__ $$acomputer$$bc$$2rdamedia
001435863 338__ $$aonline resource$$bcr$$2rdacarrier
001435863 4901_ $$aStatistics for biology and health,$$x1431-8776
001435863 504__ $$aIncludes bibliographical references and index.
001435863 5050_ $$aPrinciples of Experimental Design -- Review of Statistical Concepts -- Planning for Precision and Power -- Comparing More than Two Groups -- Comparing Treatment Groups with Linear Contrasts -- Multiple Treatment Factors: Factorial Designs -- Improving Precision and Power: Blocked Designs -- Split-Unit Designs -- Many Treatment Factors: Fractional Factorial Designs -- Experimental Optimization with Response Surface Methods -- References -- Index.
001435863 506__ $$aAccess limited to authorized users.
001435863 520__ $$aThis richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including portable power formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
001435863 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 22, 2021).
001435863 650_0 $$aExperimental design.
001435863 650_0 $$aBiology$$xExperiments$$xStatistical methods.
001435863 650_6 $$aPlan d'expérience.
001435863 650_6 $$aBiologie$$xExpériences$$xMéthodes statistiques.
001435863 655_7 $$aLlibres electrònics.$$2thub
001435863 655_0 $$aElectronic books.
001435863 77608 $$iPrint version:$$aKaltenbach, Hans-Michael.$$tStatistical design and analysis of biological experiments.$$dCham : Springer, [2021]$$z3030696405$$z9783030696405$$w(OCoLC)1233163166
001435863 830_0 $$aStatistics for biology and health.$$x1431-8776
001435863 852__ $$bebk
001435863 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-69641-2$$zOnline Access$$91397441.1
001435863 909CO $$ooai:library.usi.edu:1435863$$pGLOBAL_SET
001435863 980__ $$aBIB
001435863 980__ $$aEBOOK
001435863 982__ $$aEbook
001435863 983__ $$aOnline
001435863 994__ $$a92$$bISE