000			02960cam a22003734a 4500
001			16594710
003			OSt
005			20220527151830.0
008			101230s2011 njua b 000 0 eng
010			_a 2010054064
020			_a9780470621691 (hardback)
040			_aDLC _cHU _dDLC
042			_apcc
050	0	0	_aQA276.8 _b.Z53 2011
082	0	0	_a519.5/4 ZIE 2011 _222
084			_aSOC027000 _2bisacsh
100	1		_aZieffler, Andrew, _d1974- _936902
245	1	0	_aComparing groups : _brandomization and bootstrap methods using R / _cAndrew S. Zieffler, Jeffrey R. Harring, Jeffrey D. Long.
260			_aHoboken, N.J. : _bWiley, _cc2011.
300			_axxxii, 298 p. : _bill. ; _c25 cm.
504			_aIncludes bibliographical references (p. 287-298).
520			_a"This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computation to propose answers to specific research questions. Furthermore, practical suggestions for the analysis and presentation of results, in prose, tables and/or figures, are included. Optional sections for each chapter include methodological extensions for readers desiring additional technical details. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the authors focus on conceptual explanations and the use of statistical computing. Statistical computing is an integral part of statistical work, and to support student learning in this area, examples using the R computer program are provided throughout the book. Rather than relegate examples to the end of chapters, the authors interweave computer examples with the narrative of the book. Topical coverage includes an introduction to R, data exploration of one variable, data exploration of multivariate data - comparing two groups and many groups, permutation and randomization tests, the independent samples t-Test, the Bootstrap test, interval estimates and effect sizes, power, and dependent samples"-- _cProvided by publisher.
650		0	_aBootstrap (Statistics) _936903
650		0	_aRandom data (Statistics) _936904
650		0	_aPsychology _xData processing. _936905
650		0	_aR (Computer program language) _99240
650		0	_aDistribution (Probability theory) _93173
650		7	_aSOCIAL SCIENCE / Statistics _2bisacsh. _936906
700	1		_aHarring, Jeffrey, _d1964- _936907
700	1		_aLong, Jeffrey D., _d1964- _936908
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBOOKS _n0
999			_c35490 _d35490