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 ...
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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 students and researchers library.
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Add this copy of Understanding Regression Assumptions to cart. $18.47, good condition, Sold by ThriftBooks-Reno rated 4.0 out of 5 stars, ships from Reno, NV, UNITED STATES, published 1993 by Sage Publications, Inc.
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Good. Trade paperback (US). Glued binding. 104 p. Contains: Illustrations. Quantitative Applications in the Social Sciences, 92. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
