Data Exploration – Cluster Analysis

Cluster Analysis (Descriptive Statistics) examines how variables or individuals are grouped. The visual representation is often referred to as a dendrogram,  as groups are clustered into tree branches.

To perform this analysis – select cluster from Descriptive Statistics:

Screen shot 2016-03-01 at 8.15.36 PM


Next step is to select your dependent variable (response) from your uploaded CSV file. Dependent variable can be binary (e.g. yes, no), continuous (e.g. 1,2,3) or multinomial (e.g. deletion, retention, aspiration). Final step is to choose your independent factor – make sure it has at least three values. For instance, I have my file with a dependent variable (Object-Verb/Verb-Object) from my data on Old French texts. I would like to examine how  different genres are grouped according to their use of word order. So I select “genre” as my independent factor, which has more than three values.

Screen shot 2016-03-01 at 8.12.32 PM

I can see from the graph that there are three clusters in my data: 1) letters and treatise, 2) speech and hagio, and 3) narratives.


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