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parametric statistics - select the appropriate statistical procedure, yes, logit and probit models, parametric statistics - select the appropriate statistical procedure, unique overlap, multivariate analysis of variancece (manova) , design ii, 1, yes, two-way anova, multiple exogenous and endogenous observed variables, techniques, no, biavariate multivariate continggency table analysis crosstabulation, 2 , 1, contionous, bivariate correlation, this may be redundand, see what you can should add to above diagram, 2 , design i, analysis of variance & multiple regression, yes, multidemensional scaling, no, disregard overlap, select the appropriate statistical test, t tests, no, ? this diagram is messed up, see page 143, multivariate, nonparametric tests, logilinear models, factorial anova, no, no, factor analysis, one-way anova or t test, methodology, or b) use canonical correlation, one-way anova, design iv, can teh she scores or value sof the ivs discriimate groups, or predict group membership, note techniques to deal with multiple dvs are notot availalbe, 1, univariate tests, anzlye multiple dvs independently, yes, bivariate tests, multiple regression, 2 , multiple disrcrimant fucntion analyisis, bivariate correlation, strucural equation modeling, a special case of canonical correlation multiple exogenous variables that usually represent group membereship multiple endogenous observed variables , logit, 1, yes, or, use controls with other dvs, cluster analysis, partial correlation, yes, degree of strength of relationship between iv and dv, multiple regression correlation (hierarchical), design iii, contionous, 2 , discrete, probit analysis, are there sig. group differences between the groups formed by the iv(s) and scores on teh dv, logistic regression, no, discrete, or c) utilize path analysis or sem, are differnces in the frequency of occurrence of the iv realted to differences in the frequency of occurence of the ivs?, no, are teh scores on the ivs significantly relate to teh categegories formed by teh dv? , hierarchical analysis, regression, multiple regression correlation, one-way ancova, experiment w blocks, 2 , discrete, yes, a) analyze each independently , dsicriimant function n analysis (hiearchical if covvariates are present), eta, f distribuion, 1, factorial ancova, yes, contionous, logistic regressionn, crosstabulations, no, multiple discriminant functions, polytomous logistic regression