000			03420cam a22003374a 4500
001			16698238
003			BD-DhUL
005			20140807123925.0
008			110318s2012 caua b 001 0 eng
010			_a 2011009895
020			_a9781412974066 (pbk. : alk. paper)
040			_aDLC _cDLC _dDLC _dBD-DhUL
042			_apcc
050	0	0	_aHA32 _b.B47 2012
082	0	0	_a005.55 _222 _bBEC
100	1		_aBerkman, Elliot T.
245	1	2	_aA conceptual guide to statistics using SPSS / _cElliot T. Berkman, Steven P. Reise.
260			_aLos Angeles : _bSage, _cc2012.
300			_axiii, 296 p. : _bill. ; _c24 cm.
365			_aUSD _b37.13
504			_aIncludes bibliographical references and indexes.
505	8		_aMachine generated contents note: 1. Introduction 2. Descriptive Statistics 3. Chi-Squared Test 4. Linear Correlation 5. One- and Two Sample T-Tests 6. One-way ANOVA 7. Two- and Higher-way ANOVA 8. Within-subject ANOVA 9. Mixed-model ANOVA 10. MANOVA 11. Regression 12. ANCOVA 13. Factor and Components Analysis 14. Psychometrics 15. Non-parametric Tests 16. Matrix Algebra 17. Appendix on the General Formulation of Custom Contrasts using Syntax .
520			_a"This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures. Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics"-- _cProvided by publisher.
630	0	0	_aSPSS for Windows.
650		0	_aStatistics _xComputer programs.
650		0	_aSocial sciences _xStatistical methods _xComputer programs.
700	1		_aReise, Steven Paul.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
955			_bxj07 2011-03-18 _cxj07 2011-03-18 ONIX _axd13 2011-03-22 changed copyright per publisher _axe06 2011-07-20 1 copy rec'd., to CIP ver.
999			_c1128 _d1128