We, humans, are apparently prone to likely believing numbers and data when they are presented on any screen. I learned this amazing thing when recording a podcast with someone I personally think is among the best data scientists on the continent, Dr. Vukosi Marivate.
Have you noticed how you are more likely to believe (without proof) any number presented by a news reporter?
Which is partly why there has been a welcome trend in βdata-informedβ decision making in various sectors. However, not all data is necessarily fact or is presenting you with a useful βpictureβ from which to make a decision.

Today I read an article that said that Cape Townβs decision makers have decided that people under 55 years old will no longer be tested for COVID-19. For the purposes of this newsletter it is not the health debate I am concerned with but the 2nd order effects such a decision has on the data that will be presented to the public and policymakers.
This decision likely means that from the data collected going forward compared to previous data, Cape Town is likely to have a documented (data-informed) decrease in COVID-19 cases. A picture which might fool some who donβt scratch the surface to understand how the data was collected and also from where.
Because even when we are talking about data, biases have a way of creeping in.
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