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The Nature of Data
Summary Indices for Bivariate Relationships
Other Indices of Relationship for Two Variables
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angle assumption axes axis bivariate canonical analysis canonical correlation chapter cluster analysis common variance communality component loadings computed considered correlation coefficient correlation matrix correlation ratio criterion variable cross-validation cutting score defined described developed deviation scores dimensions discriminant function discussed distribution eigenvalues estimate example external factor analysis factor loadings Figure formula geometric given group means group membership hypersphere individuals interpretation interval scale Kaiser criterion large number linear main diagonal maximum maximum likelihood measurement multiple correlation multivariate number of factors number of variables observed variables obtained pair partial correlation plane point biserial correlation possible prediction predictor variables problem procedures proportion of variance rank model raw score regression equation regression line regression weights relationship represent rotation sample scale scatter plot score matrix set of variables simple structure situation solution space standard deviation standard scores statistical significance sum of squared Table tion variable vectors yield zero