Dear All,

Upon analyzing the variables 'latitude' and 'longitude,' it appears that data points for two provinces—Eastern Cape (EC) and Western Cape (WC)—are entirely absent from the dataset. This exclusion raises several questions and concerns in my mind.

Firstly, I wonder why these two provinces were omitted. By excluding EC and WC, are we inadvertently creating an incomplete population in the dataset? Could this exclusion represent what is referred to as a "hidden dataset," which the model may ultimately need in order to generalize effectively?

Would it not be more appropriate to compile a hidden dataset by randomly sampling data from all provinces, rather than isolating EC and WC entirely? This approach might ensure a more representative sample while mitigating any potential data imbalance.

Additionally, could the high incidence of the 'target variable' in EC and WC have influenced this decision? If the target's prevalence is significantly higher in these regions, it may have been perceived as a potential source of bias in the dataset. That said, excluding these provinces outright could inadvertently impact the model's accuracy and fairness.

Finally, an ethical question arises: is it justifiable to exclude vulnerable populations, such as women in EC and WC, from the dataset? Ensuring that these regions are represented might provide insights that are essential to addressing their unique needs and challenges. Transparency regarding this exclusion, as well as an exploration of alternative approaches, would go a long way in fostering trust and equitable and ethical analysis.

I welcome your thoughts and perspectives on this matter. Please feel free to share your insights. These are simply my musings, and I mean no harm or offense to any stakeholders involved.

Kind regards,

Augustine aka Jaw22