As 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.... Residual Normal Probability -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 Studentized Deviance Residual 13.11 Normality seems to be satisfied and the residual plot show that the model is satisfactory. Scatterplm 01 ms: 00 [aquot;01 Probability Hot 00 DEBS!
|Title||:||Solutions Manual to Accompany Introduction to Linear Regression Analysis|
|Author||:||Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining|
|Publisher||:||John Wiley & Sons - 2013-04-23|