LEADER 03330nam 2200529z- 450 001 9910960742703321 005 20250219111929.0 010 $a9781118548509 010 $a1118548507 035 $a(CKB)6190000000004969 035 $a(MiAaPQ)EBC7103795 035 $a(EXLCZ)996190000000004969 100 $a20230424c2013uuuu -u- - 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSolutions Manual to Accompany Introduction to Linear Regression Analysis, Fifth Edition 205 $a5th ed. 210 $cJohn Wiley & Sons (US) 210 1$aSomerset :$cJohn Wiley & Sons, Incorporated,$d2013. 210 4$dİ2013. 215 $a1 online resource (105 pages) 300 $aPreface signed by Anne G. Ryan, Dana C. Krueger, Scott M. Kowalski. 311 08$a9781118471463 311 08$a1118471466 327 $aIntro -- Half Title page -- Title page -- Copyright page -- Preface -- Chapter 2: Simple Linear Regression -- Chapter 3: Multiple Linear Regression -- Chapter 4: Model Adequacy Checking -- Chapter 5: Transformations and Weighting to Correct Model Inadequacies -- Chapter 6: Diagnostics for Leverage and Influence -- Chapter 7: Polynomial Regression Models -- Chapter 8: Indicator Variables -- Chapter 9: Multicollinearity -- Chapter 10: Variable Selection and Model Building -- Chapter 11: Validation of Regression Models -- Chapter 12: Introduction to Nonlinear Regression -- Chapter 13: Generalized Linear Models -- Chapter 14: Regression Analysis of Time Series Data -- Chapter 15: Other Topics in the Use of Regression Analysis. 330 $aAs the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation. 606 $aCorrelation (Statistics) 606 $aMathematics 606 $aRegression analysis 615 0$aCorrelation (Statistics) 615 0$aMathematics. 615 0$aRegression analysis. 676 $a519.5/36 700 $aMontgomery$b Douglas C$09293 701 $aPeck$b Elizabeth A$020687 701 $aVining$b G Geoffrey$0266109 701 $aRyan$b Ann G$01789315 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910960742703321 996 $aSolutions Manual to Accompany Introduction to Linear Regression Analysis, Fifth Edition$94324811 997 $aUNINA