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Applied regression modeling DUP_1

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applied regression modeling DUP_1/ Iain Pardoe.
作者:	Pardoe, Iain,
出版者:	Hoboken, NJ :Wiley, : 2012.,
面頁冊數:	1 online resource.
標題:	Regression analysis. -
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9781118345054
ISBN:	9781118345047 ( epub)

Applied regression modeling DUP_1
Pardoe, Iain,1970-

Applied regression modeling DUP_1[electronic resource] /Iain Pardoe. - 2nd ed. - Hoboken, NJ :Wiley,2012. - 1 online resource.

Includes bibliographical references and index.

Front Matter -- Foundations -- Simple Linear Regression -- Multiple Linear Regression -- Regression Model Building I -- Regression Model Building II -- Case Studies -- Extensions -- Appendix A: Computer Software Help -- Appendix B: Critical Values for t-Distributions -- Appendix C: Notation and Formulas -- Appendix D: Mathematics Refresher -- Appendix E: Brief Answers to Selected Problems -- References -- Glossary -- Index.

"This book offers a practical, concise introduction to regression analysis for upper-level undergraduate students of diverse disciplines including, but not limited to statistics, the social and behavioral sciences, MBA, and vocational studies. The book's overall approach is strongly based on an abundant use of illustrations, examples, case studies, and graphics. It emphasizes major statistical software packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided on a specially prepared and maintained author web site. Select software output appears throughout the text. To help readers understand, analyze, and interpret data and make informed decisions in uncertain settings, many of the examples and problems use real-life situations and settings. The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting. New to this edition are more exercises, simplification of tedious topics (such as checking regression assumptions and model building), elimination of repetition, and inclusion of additional topics (such as variable selection methods, further regression diagnostic tests, and autocorrelation tests)"--

ISBN: 9781118345047 ( epub)

LCCN: 2012006617Subjects--Topical Terms:

569541
Regression analysis.

LC Class. No.: QA278.2

Dewey Class. No.: 519.5/36

Applied regression modeling DUP_1
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020 $a 1118345053 (electronic bk.)
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020 $a 1118274415 (electronic bk.)
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082 0 0 $a 519.5/36 $2 23
100 1 $a Pardoe, Iain, $d 1970- $3 1059662
245 1 0 $a Applied regression modeling DUP_1 $h [electronic resource] / $c Iain Pardoe.
250 $a 2nd ed.
260 $a Hoboken, NJ : $b Wiley, $c 2012.
300 $a 1 online resource.
504 $a Includes bibliographical references and index.
505 0 $a Front Matter -- Foundations -- Simple Linear Regression -- Multiple Linear Regression -- Regression Model Building I -- Regression Model Building II -- Case Studies -- Extensions -- Appendix A: Computer Software Help -- Appendix B: Critical Values for t-Distributions -- Appendix C: Notation and Formulas -- Appendix D: Mathematics Refresher -- Appendix E: Brief Answers to Selected Problems -- References -- Glossary -- Index.
520 $a "This book offers a practical, concise introduction to regression analysis for upper-level undergraduate students of diverse disciplines including, but not limited to statistics, the social and behavioral sciences, MBA, and vocational studies. The book's overall approach is strongly based on an abundant use of illustrations, examples, case studies, and graphics. It emphasizes major statistical software packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided on a specially prepared and maintained author web site. Select software output appears throughout the text. To help readers understand, analyze, and interpret data and make informed decisions in uncertain settings, many of the examples and problems use real-life situations and settings. The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting. New to this edition are more exercises, simplification of tedious topics (such as checking regression assumptions and model building), elimination of repetition, and inclusion of additional topics (such as variable selection methods, further regression diagnostic tests, and autocorrelation tests)"-- $c Provided by publisher.
588 $a Description based on print version record and CIP data provided by publisher.
650 0 $a Regression analysis. $3 569541
650 0 $a Statistics. $3 556824
856 4 0 $u http://onlinelibrary.wiley.com/book/10.1002/9781118345054