Applied Regression Analysis, Volume 1This book provides a standard, basic course in multiple linear regression, but it also includes material that either has not previously appeared in a textbook or, if it has appeared, is not generally available. |
Contents
CHAPTER PAGE | 1 |
THE MATRIX APPROACH TO LINEAR REGRESSION | 44 |
THE EXAMINATION OF RESIDUALS | 86 |
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actually additional analysis of variance ANOVA Source appear apply b₁ calculations Chapter Coefficients column confidence Confidence Limits Constant Control correct Correlation Coefficients corresponding defined degrees of freedom dependent Determinant df SS discussed distribution effect elements entering equation error estimate examined example explained F Total Figure follows function given independent variables indicates interval involved lack of fit least squares linear matrix mean mean square measure method multiple nonlinear normal equations Note observations obtained occur original Overall parameters plot possible prediction prediction equation problem procedure pure error regression regression equation Requirements residuals response runs selected shown significant situation space Square of Partials stage Standard Standard deviation Statistical Step sum of squares Suppose temperature transformations true usually variation vector write X₁ Y₁ zero