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Understanding Regression Assumptions
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Understanding Regression Assumptions



February 1993 | 104 pages | SAGE Publications, Inc

Through the use of careful explanations and examples, Berry shows the reader how to consider whether the assumptions of multiple regression are actually satisfied in a particular research project. Beginning with a brief review of the regression assumptions as they are typically presented in textbooks, Berry moves on to explore in detail the "substantive" meaning of each assumption (such as lack of measurement error, absence of specification error, linearity, homoscedasticity, and lack of autocorrelation). Aimed at improving social science applications of regression, this volume is a must for every student's and researcher's library.


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Introduction
 
A Formal Presentation of the Regression Assumptions
 
A `Weighty' Illustration
 
The Consequences of the Regression Assumptions Being Satisfied
 
The Substantive Meaning of Regression Assumptions
 
Conclusion

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