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Understanding regression assumptions

Author: William Dale Berry
Publisher: Newbury Park, Calif. : Sage Publications, ©1993.
Series: Quantitative applications in the social sciences, no. 07-092.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Through the use of careful explanation and examples, Berry demonstrates how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Berry, William Dale.
Understanding regression assumptions.
Newbury Park, Calif. : Sage Publications, ©1993
(DLC) 92042925
(OCoLC)27067328
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: William Dale Berry
ISBN: 058521722X 9780585217222 9781412986427 1412986427
OCLC Number: 44963120
Description: 1 online resource (vii, 91 pages) : illustrations.
Contents: 1. Introduction --
2. A formal presentation of the regression assumptions --
The regression surface --
The role of the error term --
Other regression assumptions --
3. A "weighty" illustration --
4. The consequences of the regression assumptions being satisfied --
5. The substantive meaning of regression assumptions --
Drawing dynamic inferences from cross-sectional regressions --
The assumption of the absence of perfect multicollinearity --
The assumption that the error term is uncorrelated with each of the independent variables --
Specification error: using the wrong independent variables --
The assumption that the mean of the error term is zero --
Assumptions about level of measurement --
The assumption of measurement without error --
Random measurement error --
Nonrandom measurement error --
Proxy variables --
The assumptions of linearity and additivity --
The assumption of homoscedasticity and lack of autocorrelation --
The substantive meaning of autocorrelation --
The substantive meaning of homoscedasticity --
The consequences of heteroscedasticity and autocorrelation --
The assumption that the error term is normally distributed --
6. Conclusion.
Series Title: Quantitative applications in the social sciences, no. 07-092.
Responsibility: William D. Berry.
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Abstract:

Through the use of careful explanation and examples, Berry demonstrates how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project.

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