Statistical Principles in Experimental Design
An experimental design text for advanced level courses in behavioural sciences. The logic basic to understanding principles underlying the statistical aspects of experimental design is emphasized rather than the details of mathematical and statistical proofs. This edition has been fully updated, but still requires that the student have statistical inference as a prerequisite.
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Introduction to Design
SingleFactor Experiments Having Repeated
Procedures and Numerical Examples
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adjusted analysis of variance appropriate approximation associated assumed assumptions blocks cell coefficients column comparison complete components computational confounded considered correlation corresponding covariance critical value defined degrees of freedom denominator dependent differences distribution drug elements entries equal equation error estimate example expected values experimental expression F ratio factorial experiment fixed function given groups Hence homogeneity hypothesis illustrated independent indicates interaction interest latter levels of factor linear main effects matrix mean squares methods MSerror normal notation notes observations obtained overall parameters Plan population possible predicted presented probability procedures provides random regression reject relation relative replication represents residual respect sample sampling distribution simple Source of variation statistic subjects summary Suppose symbol Table treatment treatment combinations variable variation due vector zero