000			01869nam a22002538a 4500
999			_c27458 _d27458
001			61994
010			_a 2015011813
020			_a9781483381473
040			_aDLC
082	0	0	_a519.5/36
100	1		_aLewis-Beck, Colin _958913
245	1	0	_aApplied regression : _ban introduction _cColin, Lewis-Beck, Michael S. Lewis-Beck
250			_a2nd ed.
260			_aLos Angeles : _bSage, _cc2016.
300			_axvi, 103 p. : _bill ; _c21 cm.
490			_aQuantitative applications in the social sciences ; _vVol. no. 07-022
504			_aIncludes bibliographical references and index.
505	0		_aSeries Editor's Introduction Preface Acknowledgments About the Authors 1. Bivariate Regression: Fitting a Straight Line 2. Bivariate Regression: Assumptions and Inferences 3. Multiple Regression: The Basics 4. Multiple Regression: Special Topics Appendix References Index.
520			_aKnown for its readability and clarity, this Second Edition provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. The authors then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.
650		0	_aRegression analysis _910679
700			_aLewis-Beck, Michael S. _958914
856			_uhttps://uowd.box.com/s/qb1me0s3046evk008bsvl8f0v0cngh64 _zLocation Map
942			_cREGULAR _2ddc