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2012006617 contributor B12434560.
2012006617 created "2012.".
2012006617 date "2012".
2012006617 date "2012.".
2012006617 dateCopyrighted "2012.".
2012006617 description "Description based on print version record and CIP data provided by publisher; resource not viewed.".
2012006617 description "Machine generated contents note: Preface xiAcknowledgments xviiIntroduction xvii1.1 Statistics in practice xvii1.2 Learning statistics xix1. Foundations 11.1 Identifying and summarizing data 11.2 Population distributions 51.3 Selecting individuals at random--probability 91.4 Random sampling 111.5 Interval estimation 151.6 Hypothesis testing 191.7 Random errors and prediction 251.8 Chapter summary 28Problems 292. Simple linear regression 352.1 Probability model for X and Y 352.2 Least squares criterion 402.3 Model evaluation 452.4 Model assumptions 592.5 Model interpretation 662.6 Estimation and prediction 682.7 Chapter summary 72Problems 783. Multiple linear regression 833.1 Probability model for (X1; X2; : : : ) and Y 833.2 Least squares criterion 873.3 Model evaluation 923.4 Model assumptions 1183.5 Model interpretation 1243.6 Estimation and prediction 1263.7 Chapter summary 130Problems 1324. Regression model building I 1374.1 Transformations 1384.2 Interactions 1594.3 Qualitative predictors 1664.4 Chapter summary 182Problems 1845. Regression model building II 1895.1 Influential points 1895.2 Regression pitfalls 1995.3 Model building guidelines 2185.4 Model selection 2215.5 Model interpretation using graphics 2245.6 Chapter summary 231Problems 2346. Case studies 2436.1 Home prices 2436.2 Vehicle fuel efficiency 2536.3 Pharmaceutical patches 2617. Extensions 2677.1 Generalized linear models 2687.2 Discrete choice models 2757.3 Multilevel models 2787.4 Bayesian modeling 280Appendix A. Computer software help 285Appendix B. Critical values for t distributions 289Appendix C. Notation and formulas 293Appendix D. Mathematics refresher 297Appendix E. Answers to selected problems 299References 309Glossary 315Index 321.".
2012006617 extent "1 online resource.".
2012006617 hasFormat "Applied regression modeling".
2012006617 identifier "9781118345023 (pdf)".
2012006617 identifier "9781118345030 (mobi)".
2012006617 identifier "9781118345047 ( epub)".
2012006617 isFormatOf "Applied regression modeling".
2012006617 issued "2012".
2012006617 issued "2012.".
2012006617 language "eng".
2012006617 publisher "Hoboken, NJ : Wiley,".
2012006617 relation "Applied regression modeling".
2012006617 subject "519.5/36 23".
2012006617 subject "MATHEMATICS / Probability & Statistics / Regression Analysis. bisacsh".
2012006617 subject "QA278.2".
2012006617 subject "Regression analysis.".
2012006617 subject "Statistics.".
2012006617 tableOfContents "Machine generated contents note: Preface xiAcknowledgments xviiIntroduction xvii1.1 Statistics in practice xvii1.2 Learning statistics xix1. Foundations 11.1 Identifying and summarizing data 11.2 Population distributions 51.3 Selecting individuals at random--probability 91.4 Random sampling 111.5 Interval estimation 151.6 Hypothesis testing 191.7 Random errors and prediction 251.8 Chapter summary 28Problems 292. Simple linear regression 352.1 Probability model for X and Y 352.2 Least squares criterion 402.3 Model evaluation 452.4 Model assumptions 592.5 Model interpretation 662.6 Estimation and prediction 682.7 Chapter summary 72Problems 783. Multiple linear regression 833.1 Probability model for (X1; X2; : : : ) and Y 833.2 Least squares criterion 873.3 Model evaluation 923.4 Model assumptions 1183.5 Model interpretation 1243.6 Estimation and prediction 1263.7 Chapter summary 130Problems 1324. Regression model building I 1374.1 Transformations 1384.2 Interactions 1594.3 Qualitative predictors 1664.4 Chapter summary 182Problems 1845. Regression model building II 1895.1 Influential points 1895.2 Regression pitfalls 1995.3 Model building guidelines 2185.4 Model selection 2215.5 Model interpretation using graphics 2245.6 Chapter summary 231Problems 2346. Case studies 2436.1 Home prices 2436.2 Vehicle fuel efficiency 2536.3 Pharmaceutical patches 2617. Extensions 2677.1 Generalized linear models 2687.2 Discrete choice models 2757.3 Multilevel models 2787.4 Bayesian modeling 280Appendix A. Computer software help 285Appendix B. Critical values for t distributions 289Appendix C. Notation and formulas 293Appendix D. Mathematics refresher 297Appendix E. Answers to selected problems 299References 309Glossary 315Index 321.".
2012006617 title "Applied regression modeling [electronic resource] / Iain Pardoe.".
2012006617 type "text".