Mean-Absolute-Deviation-Packaging

Packing functions to be integrated into developing software, the Quality Compute Engine. Mean Absolute Deviation can be derived from talking degree centrality values and averaging them to analyze brain data. Using Mean Absolute Deviation from degree centrality because degree centrality is defined as the number of links incident upon a node (i.e., the number of ties that a node has) thus, it could inform us of the clustering without using k-means. We could then take make a statement such as if you are below x average intensity and y standard deviation, we recommend investigating for black tiles or upload errors.