transforms correlations among a set of observed variables into smaller number of factors, containing essential information about the linear inter-relationships among the original test scores (Kriegel, Kroger, Sander, & Zimek, 2011). Factor analysis is used in behavioral sciences, social sciences, and other applied sciences dealing with large quantities of data. In addition, factor analysis is subdivided into two major groups; exploratory and confirmatory. Cluster analysis on the other hand entails dividing a set of variables into groups; clusters with data in the same cluster being similar to each other as opposed to those in other clusters. Cluster analysis is mainly used in statistical analyses such as information retrieval, and bioinformatics. Just like factor analysis, cluster analysis has two subgroups; exploratory and confirmatory.

Q-sort vs. R-sort Factor and Cluster Analyses

In both factor and cluster analysis, Q-sort entails ranking sets of statements based on how strongly subjects agree or disagree with...

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