What is the primary difference between hierarchical and k$-$means clustering techniques?

k$-$means can only be used with categorical data.

Hierarchical clustering uses a fixed number of clusters while k$-$means does not.

Hierarchical clustering does not require the number of clusters to be specified in advance.

k$-$means clustering is supervised while hierarchical is unsupervised.

Both clustering methods are primarily used for predictive modeling.