When modeling data with machine learning, QSRR, and other statistically driven techniques, it is essential that curation and analysis of the relevant data is conducted. The distribution of data should be investigated as to provide insight towards internal biases, i.e. highly over-represented values, and other anomalies that could complicate modeling or bias models.