Description: Regression DiagnosticsAn Introduction Author(s): John Fox Format: Paperback Publisher: SAGE Publications Inc, United States Imprint: SAGE Publications Inc ISBN-13: 9781544375229, 978-1544375229 Synopsis Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website.
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Book Title: Regression Diagnostics
Item Height: 215 mm
Item Width: 139 mm
Series: Quantitative Applications in the Social Sciences
Author: John Fox
Publication Name: Regression Diagnostics: an Introduction
Format: Paperback
Language: English
Publisher: SAGE Publications INC International Concepts
Subject: Mathematics
Publication Year: 2020
Type: Textbook
Number of Pages: 168 Pages