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Regression Analysis by Example

By: Contributor(s): Material type: TextTextLanguage: English Series: Wiley Series in Probability and Mathematical StatisticsPublication details: USA John Wiley & Sons 2000Description: xv, 359 pages illustrations 24 cmISBN:
  • 0471319465
  • 9780471319467
Patent information: 1999Subject(s): DDC classification:
  • 519.5/36 21
LOC classification:
  • QA278.2 .C5 2000
Contents:
Preface -- Introduction -- Simple linear regression -- Multiple linear regression -- Regression diagnostics: detection of model violations -- Qualitative variables a predictors -- Transformation of variables -- Weighted least squares -- The problem of correlated errors -- Analysis of collinear data -- Biased estimation of regression coefficients -- Variable selection procedures -- Logistic regression
Review: "Suitable for anyone with an understanding of elementary statistics, Regression Analysis by Example, Third Edition illustrates methods of regression analysis, with examples containing the types of irregularities commonly encountered in the real world. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. Each of the methods described can be carried out with most currently available statistical software packages."--Jacket
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Preface -- Introduction -- Simple linear regression -- Multiple linear regression -- Regression diagnostics: detection of model violations -- Qualitative variables a predictors -- Transformation of variables -- Weighted least squares -- The problem of correlated errors -- Analysis of collinear data -- Biased estimation of regression coefficients -- Variable selection procedures -- Logistic regression

"Suitable for anyone with an understanding of elementary statistics, Regression Analysis by Example, Third Edition illustrates methods of regression analysis, with examples containing the types of irregularities commonly encountered in the real world. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. Each of the methods described can be carried out with most currently available statistical software packages."--Jacket

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