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1

If outliers in your data cause a negative skew, the most appropriate transformation strategy is to use a .
2

If an examination of a scatterplot of your data shows a conical pattern, then is present.
3

The most popular rotation strategy in factor analysis is .
4

is a correlational technique that allows you to evaluate the relationship between two variables with the effects of a third removed from both of them.
5

The general linear equation formula is .
6

In the absence of any theoretical ordering of variables, is the multiple regression strategy of choice.
7

is the correlation between predicted values of Y and the observed values of Y, whereas is the proportion of variability in the dependent variable that is accounted for by a set of predictors.
8

The regression weights are usually used to interpret a significant regression analysis because they express differently scaled variables in the same terms.
9

Although a regression weight is often used as an index of the degree of contribution of a predictor variable, a better index is the .
10

The number of possible discriminant functions in a discriminant analysis is limited to or to , whichever is less.
11

To determine the relationship between two sets of variables, you would use .
12

The produced in an SPSS-X MANOVA output are similar to factor loadings and can be used to evaluate the degree of contribution of a variable.
13

A path model that has causal relationships that run in only one direction and have no causal loops is called a(n) model.
14

are used to estimate the degree of causal relationship between variables in a path model.
15

are followed when decomposing a path model into direct and indirect effects.
16

According to your text, you should when considering using multivariate statistics.







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