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Data Representation and Transformation
Linear Models and The Analysis of Variance
14 other sections not shown
analysis of variance assume assumptions block SS calculate causal cell column completely randomized design confounded consistency criterion correlation corresponding covariance defined degrees of freedom dependent variable discussed disturbance terms equal error SS example exogenous variables expected value experimental F ratio factorial effect factorial experiment factors Fortran full model given hypotheses independent indicators inferences interaction involving least-squares estimates linear main effect matrix mean measurement-error multiple nonadditivity nonrandom notation null hypothesis obtained ordinary least squares parameters partial path coefficients possible predicted procedure produce question random measurement random measurement errors recursive regression SS relationship replication represent residual restricted model sampling error scores shown in Table side conditions significance situation specific SS due statement statistical SUBROUTINE Suppose technique theoretical total SS treatment combinations treatment effects treatment SS true units unknown weights variation vector zero