Using Multivariate Statistics"Using Multivariate Statistics" provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. |
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Contents
Using | 20 |
Review of Univariate and Bivariate | 33 |
Screening Data Prior | 58 |
Copyright | |
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Common terms and phrases
addition adjusted analysis assessed association assumption ATTHOUSE attitudes ATTROLE canonical canonical variates cell Chapter classification coefficients combination comparisons considered continuous contrasts CONTROL correlation correlation matrix covariates degrees of freedom deleted DEPENDENT deviations differences discriminant function discussed distribution effects eigenvalues ENTER equal equation error estimates evaluated example expected factors Figure frequencies groups hierarchical homogeneity important included interaction interpretation labeled levels linear loadings main effect MANOVA marginal matrix means measures methods missing multiple multivariate NAMES NEVER normality observed outliers output pairs parameter partial plots predicted predictors problem procedures produce programs provides regression relationship reliable residuals rotation sample scores SELECTED separate SETUP shows significant skewness solution SPSS standard statistical step subjects sum of squares SYSTAT Table transformation treatment univariate values variables variance women Yes Yes Yes