Exam 17: Basic Multivarate Techniques

The log function variable equation form is:

In ensuring that variables are theoretically independent, a researcher is really:

In choosing the appropriate statistical procedure to test a causal model, one must:

By using the BACKWARD option within regression analysis, whereby all variables are included in the analysis and the least important ones are dropped, the advantage is:

To test an intervening variable model with PARTIAL CORR, which of the following must also be employed:

The source of spuriousness model suggests that:

The MEANS solution (regression analysis):

To fully demonstrate that a relationship is not spurious is:

When the source of spuriousness variable is controlled for, and the model turns out to be correct, then the original relationship between X and Y must have:

When variables are converted to log function variables, the new equation becomes:

Discriminant function analysis attempts to:

Before testing a source of spuriousness model, the original relationship between X and Y must have been demonstrated as being:

R² is a measure of the:

Multiple regression analysis attempts to:

Beta weights can be profitably thought of as:

A source of spuriousness model posits that a statistically significant relationship between X and Y:

The importance of defining a mathematical equation to describe the relationship between an independent and dependent variable is:

A first-order partial takes into account:

To accept a 4 variable causal model (A ► B ► C ► D),.which of the following conditions must be satisfied:

As the number of actual, as opposed to missing, cases nears the number of variables, which of the following may occur: