Regression diagnostics

Shuangzhe Liu; Alan Welsh

doi:10.1007/978-3-642-04898-2_484

Regression diagnostics

Shuangzhe Liu, Alan Welsh

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Entry for encyclopedia/dictionary

Abstract

Regression diagnostics are a set of mostly graphical methods which are used to check empirically the reasonableness of the basic assumptions made in the model. These informal methods are an important part of regression modelling: many formal conclusions and inferences (including confidence intervals, statistical tests, prediction etc.) derived from a fitted model only make sense if the assumptions of the model hold. If the regression assumptions are violated, any application of results obtained from the model can be very misleading.

Original language	English
Title of host publication	International Encyclopedia of Statistical Science
Editors	Miodrag Lovric
Place of Publication	Berlin
Publisher	Springer
Pages	1206-1208
Number of pages	3
ISBN (Electronic)	9783642048982
ISBN (Print)	9783642048975
DOIs	https://doi.org/10.1007/978-3-642-04898-2_484
Publication status	Published - 2011

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10.1007/978-3-642-04898-2_484

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title = "Regression diagnostics",

abstract = "Regression diagnostics are a set of mostly graphical methods which are used to check empirically the reasonableness of the basic assumptions made in the model. These informal methods are an important part of regression modelling: many formal conclusions and inferences (including confidence intervals, statistical tests, prediction etc.) derived from a fitted model only make sense if the assumptions of the model hold. If the regression assumptions are violated, any application of results obtained from the model can be very misleading.",

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AB - Regression diagnostics are a set of mostly graphical methods which are used to check empirically the reasonableness of the basic assumptions made in the model. These informal methods are an important part of regression modelling: many formal conclusions and inferences (including confidence intervals, statistical tests, prediction etc.) derived from a fitted model only make sense if the assumptions of the model hold. If the regression assumptions are violated, any application of results obtained from the model can be very misleading.

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Regression diagnostics

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