Regression Analysis
Concepts and Applications
Duxbury Press
Published on 1. January 1994
Book
Hardback
650 pages
978-0-534-19869-5 (ISBN)
Description
The focus of the text is on thinking clearly about and solving practical statistical problems. The approach leads from the theoretical (meaning conceptual not mathematical) to the applied, with the concept being that samples (theory) tell the investigator what needs to be known about populations (application). The authors stress regression in practice and assume that a population has a finite number of elements, which is always the case in real problems.
The focus of the text is on thinking clearly about and solving practical statistical problems. The approach leads from the theoretical (meaning conceptual not mathematical) to the applied, with the concept being that samples (theory) tell the investigator what needs to be known about populations (application). The authors stress regression in practice and assume that a population has a finite number of elements, which is always the case in real problems.
The focus of the text is on thinking clearly about and solving practical statistical problems. The approach leads from the theoretical (meaning conceptual not mathematical) to the applied, with the concept being that samples (theory) tell the investigator what needs to be known about populations (application). The authors stress regression in practice and assume that a population has a finite number of elements, which is always the case in real problems.
More details
Language
English
Place of publication
United States
Publishing group
Cengage Learning, Inc
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 241 mm
Width: 190 mm
Weight
1270 gr
ISBN-13
978-0-534-19869-5 (9780534198695)
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Schweitzer Classification
Persons
Content
Review of statistics and matrices; regression and prediction; straight line regression; multiple linear regression; diagnostic procedures; applications of regression I; applicationa of regression II; alternate assumptions for regression; nonlinear regression.