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Other Models for the Analysis of Variance
The Assumptions of the Analysis of Variance
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analysis applied approximation average becomes block called Chapter classification coefficients column components condition consider constant correlation corresponding d.fr defined depends derive determined discrimination discussed dispersion distribution effects elements equal equation equivalent errors estimator Example Exercise expected experiment expression fact factors fitted fixed follows frequencies function further given gives groups hence holds hypothesis independent interactions intervals known latent roots linear matrix mean method moving multiple normal observations obtain original parameters particular population possible practice probabilities problem procedure random ratio reduces regression replacement require Residual sample sample mean scheme seasonal seen selected simple squares stage statistic Suppose Table theory transformation treatment trend unbiassed units usual values variables variance variation vector weights write zero