One of the hardest problems to deal with in data analysis is bias, and the biggest reason is that the general population does not understand what bias is. The common understanding of bias even in the context of data is intentional or unintentional skewing of results, typically from a flaw in the human performing or interpreting the measurement. But there are many other forms of bias, including those we are fully aware of at the time of measurement and interpretation but can do nothing about. Here is a 6 minute video summarizing a few such examples in a health screening context, but such examples are not limited to health screening. https://lnkd.in/gYzB5pgY

Sources:
https://youtu.be/BtvWMRUALeg
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