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The Matrix Approach to Linear Regression
The Examination of Residuals
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analysis of variance calculations Chapter Coefficients and Confidence column confidence interval Confidence Limits Constant Term correlation matrix Decoded B Limits degrees of freedom Determinant value deviation of residuals dummy variables estimate of a2 estimation space example F value Figure fitted equation follows function given independent variables lack of fit least squares estimate linear regression method multiple regression nonlinear normal equations Observed Y Predicted obtained orthogonal polynomials parameters Partial Correlation Coefficients Partial F-test Percent variation explained plot Predicted Y Residual prediction equation procedure pure error regression analysis regression equation Regression Variables Square Residual Analysis Residual Normal Deviate response mean Response variable Sequential F-test shown Source df SS Source of Variation squares due Squares of Partial SS MS F Standard deviation Standard Error sum of squares Term in Prediction Total corrected Total Regression Residual transformations Variable entering variance table vector zero