Applied regression modeling /
Pardoe, Iain, 1970-
Applied regression modeling / Iain Pardoe. - 2nd ed. - Hoboken, NJ : Wiley, 2012. - 1 online resource.
Includes index.
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)"--
9781118345047 1118345045 9781118345023 1118345029 9781118345030 1118345037 9781118345054 1118345053 9781118274415 1118274415 1118097289 9781118097281 9781283700283 128370028X
10.1002/9781118345054 doi
10.1002/9781118274415 Wiley InterScience http://www3.interscience.wiley.com
2012006617
Regression analysis.
Statistics.
MATHEMATICS--Probability & Statistics--Regression Analysis.
Regression analysis.
Statistics.
Electronic books.
QA278.2
519.5/36
Applied regression modeling / Iain Pardoe. - 2nd ed. - Hoboken, NJ : Wiley, 2012. - 1 online resource.
Includes index.
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)"--
9781118345047 1118345045 9781118345023 1118345029 9781118345030 1118345037 9781118345054 1118345053 9781118274415 1118274415 1118097289 9781118097281 9781283700283 128370028X
10.1002/9781118345054 doi
10.1002/9781118274415 Wiley InterScience http://www3.interscience.wiley.com
2012006617
Regression analysis.
Statistics.
MATHEMATICS--Probability & Statistics--Regression Analysis.
Regression analysis.
Statistics.
Electronic books.
QA278.2
519.5/36