Exam 21: Multivariate Data Analysis: Analytics With Interdependence Techniques

Which type of variance is external to variables and may include factors such as faulty measurement?

In factor analysis,the most common decision is to retain the number of factors that display an eigenvalue of at least ____________________.

Explain how cluster analysis can identify market segments.

Multivariate techniques that try to group things together are known as ____________________ methods.

Factor rotation is a mathematical way of simplifying factor results.

The most common rule for extracting factors in factor analysis is to base the number of factors on the number of eigenvalues greater than 5.0

Discuss the three purposes for factor analysis and the corresponding analytical approach for each.

Which term is used for results that neatly line up variables with only a single factor?

Which multivariate analysis statistically identifies a reduced number of underlying dimensions from a larger number of measured variables?

Composite factor scores are numbers that represent an individual respondent's score on each individual latent factor.

Factor analysis accomplishes data reduction by capturing means from many variables with a single variate.

In factor analysis,what does the researcher seek during data reduction?

Which factor rotation technique produces factors that represent the degree of correlation among factors?

A(n)____________________ graphs eigenvalues against the number of factors.

The specific variance is the source of variance that is common to all variables.

Which term is used when a variable has relatively high correlations with more than one factor?

The two types of multivariate techniques are ____________________ methods and ____________________ methods.

Varimax is the least common type of factor rotation.

A scree plot provides a mathematical calculation that indicates where the addition of one more factor adds little additional common variance.

A researcher has 57 variables in a large dataset and wishes to summarize the information from them into a reduced set of variables.Which multivariate technique should be used?