By Samprit Chatterjee

ISBN-10: 0470887168

ISBN-13: 9780470887165

ISBN-10: 1118532848

ISBN-13: 9781118532843

**A entire Account for info Analysts of the equipment and functions of Regression Analysis.**

Written by way of verified specialists within the box, the aim of the *Handbook of Regression research *is to supply a pragmatic, one-stop reference on regression research. the focal point is at the instruments that either practitioners and researchers use in actual lifestyles. it's meant to be a entire choice of the speculation, tools, and purposes of regression tools, however it has been intentionally written at an obtainable level.

The instruction manual offers a short and handy reference or “refresher” on rules and strategies which are worthwhile for the powerful research of information and its ensuing interpretations. scholars can use the publication as an advent to and/or precis of key techniques in regression and comparable direction paintings (including linear, binary logistic, multinomial logistic, count number, and nonlinear regression models). idea underlying the method is gifted whilst it advances conceptual figuring out and is often supplemented by means of hands-on examples.

References are provided for readers short of extra particular fabric at the themes mentioned within the publication. R code and information for the entire analyses defined within the booklet can be found through an author-maintained website.

Content:

Chapter 1 a number of Linear Regression (pages 1–21):

Chapter 2 version development (pages 23–49):

Chapter three Diagnostics for strange Observations (pages 51–65):

Chapter four ameliorations and Linearizable versions (pages 67–79):

Chapter five Time sequence facts and Autocorrelation (pages 81–109):

Chapter 6 research of Variance (pages 111–137):

Chapter 7 research of Covariance (pages 139–146):

Chapter eight Logistic Regression (pages 147–176):

Chapter nine Multinomial Regression (pages 177–190):

Chapter 10 count number Regression (pages 191–213):

Chapter eleven Nonlinear Regression (pages 215–225):