Applying regression & correlation : a guide for students and researchers .

By: Miles, JeremyContributor(s): Shevlin, MarkPublication details: London ; Thousand Oaks, Calif. : Sage Publications, 2001. Description: viii, 253 p. : ill. ; 24 cmISBN: 9780761962304Subject(s): Regression analysis | Correlation (Statistics)DDC classification: LOC classification: QA 278.2 MA 2001Summary: This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach. The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable. Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe

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Holdings
Item type	Current library	Call number	Status	Barcode
Books	FNPH LIBRARY	QA 278.2 MA 2001 (Browse shelf(Opens below))	Available	06294
Books	FNPH LIBRARY	QA 278.2 MA 2001 (Browse shelf(Opens below))	Available	06253
Books	FNPH LIBRARY	QA 278.2 MA 2001 (Browse shelf(Opens below))	Available	06254
Books	FNPH LIBRARY	QA 278.2 MA 2001 (Browse shelf(Opens below))	Available	06255
Books	FNPH LIBRARY	QA 278.2 MA 2001 (Browse shelf(Opens below))	Available	06256

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This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.
The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable.

Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe

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