We provide additional material for each method to ease the understanding and to improve your learning experience.
Cluster analysis is used to bundle objects (subjects). The aim is to combine objects to different groups (i.e., clusters) in such a way that all objects in one group are as similar to each other as possible, while the groups are as dissimilar to each other as possible.
Typical examples of research questions tackled with cluster analysis are the definition of personality types based on psychographic characteristics or the definition of market segments based on demand-relevant consumer characteristics. With a subsequent discriminant analysis, we can check to what extent the variables that were used for clustering contribute to or explain the differences between the identified clusters.