000			03064nam a22004335i 4500
988			_aSpringer_BiomedLife_2019
999			_c116735 _d116735 _x1
001			116735
003			ES-MaUEC
005			20230110040244.0
006			a||||fo|||| 00| 0
007			cr nn nnnaamaa
008			190813s2019 gw | s |||| 0|eng d
020			_a9783030034993
024	7		_a10.1007/978-3-030-03499-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA276 _b2019 EB
100	1		_aHerzog, Michael H. _eautor _9671866
245	1	0	_aUnderstanding Statistics and Experimental Design : _bHow to Not Lie with Statistics _cby Michael H. Herzog, Gregory Francis, Aaron Clarke.
250			_a1st ed. 2019.
264		1	_aCham, Switzerland _bSpringer International Publishing _c2019
300			_a1 recurso en línea (XI, 142 páginas) _b35 ilustraciones, 29 ilustraciones
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
490	0		_aLearning Materials in Biosciences _x2509-6125
490	0		_aBiomedical and Life Sciences (Springer-11642)
505	0		_aPart I -- Basic Probability Theory -- Experimental Design and the Basics of Statistics: Signal detection Theory (SDT) -- The Core Concept of Statistics -- Variations on the t-test -- PART II -- The Multiple Testing Problem -- ANOVA -- Experimental design: Model Fits, Power, and Complex Designs -- Correlation -- PART III -- Meta-analysis -- Understanding replication -- Magnitude of excess success -- Suggested improvements and challenges.
506	0		_aOpen Access
520	3		_aThis open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
650		7	_2embne _aEstadística matemática _9138936
700	1		_aFrancis, Gregory _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aClarke, Aaron _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030034986
776	0	8	_iPrinted edition: _z9783030035006
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-03499-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b01/2020 _ek _zSI