Statistical principles in experimental design
A revision of this classic statistics text for first-year graduate students in psychology, education and related social sciences. The two new authors are former students of Winer's. They have updated, rewritten and reorganized the text to fit the course as it is now taught.
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ABC2 adjusted analysis of variance assumed assumptions block effects cell frequencies chi-square distribution coefficients column comparison components computational formulas computational procedures confounded considered correlation corresponding covariance matrix criterion critical value defined degrees of freedom denominator df MS F difference drug E(MS effects of factor entries equal expected values experimental error F distribution F ratio F statistic factorial experiment given in Table Hence homogeneity indicates interaction effects Latin square latter level of significance levels of factor mean squares methods MSerror noncentral normal equations notation number of observations Numerical Example observations per cell obtained parameters Plan pooled population profiles quadratic random sample random variable regression repeated measures replication represents residual sampling distribution simple effects Source of variation subj Subjects within groups sum of squares summary table three-factor interaction treatment combinations two-factor interactions variance-covariance matrix variation due vector within-subject zero