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. |
Contents
Using | 20 |
Review of Univariate and Bivariate | 33 |
Screening Data Prior | 58 |
Copyright | |
13 other sections not shown
Common terms and phrases
adjusted analysis of variance association ATTDRUG ATTHOUSE attitudes ATTMAR ATTROLE between-subjects BMDP BMDP7M canonical correlation canonical variates cell Chapter classification correlation matrix covariates degrees of freedom deleted deviations differences DISCRIM discriminant function analysis distribution eigenvalues EMPLMNT equation error term evaluated example expected frequencies F-STATISTIC factor scores groups HAPHOUSE hierarchical homogeneity homoscedasticity interaction interpretation INTEXT kurtosis labeled LAMBDA levels linear loadings LPHYHEAL LTIMEDRS Mahalanobis distance main effect MANOVA marginal MASC means measures MENHEAL missing data missing values MSTATUS multicollinearity multiple correlation multiple regression multivariate outliers NEVER YES normality orthogonal output parameter estimates plots predicted predictors PROB procedures profile analysis programs R-SQUARED READTYP regression coefficients relationship reliable residuals rotation scatterplots Section SETUP AND SELECTED significant skewness SPSS SPSS MANOVA statistical stepdown analysis stepwise sum of squares SYSTAT Table transformation treatment Type I error univariate within-subjects women Yes Yes Yes