5.Results
The results of the Levenshtein distance measurements are analyzed in two ways. First, on the basis of the distance matrix we applied hierarchical cluster analysis (see Section 5.1). The goal of clustering is to identify the main groups. The groups are called clusters. Clusters may consist of subclusters, and subclusters may in turn consist of subsubclusters, etc. The result is a hierarchically structured tree in which the dialects are the leaves (Jain and Dubes, 1988). Several alternatives exist. We used the Unweighted Pair Group Method using Arithmetic averages (UPGMA), since dendrograms generated by this method reflected distances which correlated most strongly with the original Levenshtein distances (r=0.9832), see Sokal and Rohlf (1962).
Second, we ranked all varieties in order of relationship with the standard languages, Frisian and Town Frisian (see Section 5.2). When ranking with relation to Frisian, we looked at the average over all Frisian dialects. Since the ratings with respect to each of the Frisian varieties individually were very similar averaging was justified.
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