Solutions Manual to Accompany Introduction to Linear Regression Analysis

Author: Ann G. Ryan  

Publisher: John Wiley & Sons Inc‎

Publication year: 2014

E-ISBN: 9781118640807

P-ISBN(Paperback): 9781118471463

P-ISBN(Hardback):  9781118471463

Subject: O212.1 General statistics

Language: ENG

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Description

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.

Chapter

Chapter 3: Multiple Linear Regression

Chapter 4: Model Adequacy Checking

Chapter 5: Transforrnations and Weighting to Correct Model Inadequacies

Chapter 6: Diagnostics for Leverage and Influence

Chapter 7: Polynornial 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

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