In Data Analysis & Statistics, we often say 'Correlation is not Causation'. But what does that supposed to mean?
It is a bit of mystery for many, and even for those who think they know it's still hard to practice it in the real world.
In this seminar, Kan will walk you through why 'Correlation is not Causation', and how that becomes a problem in real life by using the mask debate over the last three years of COVID-19 pandemic as an example. He will also discuss how we can run experiments like RCT or A/B Test to distinguish between Correlation and Causation with statistical analysis.
Here is the recorded video.
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