In today’s data-driven world, we often hear terms like data and insights used interchangeably. However, there is a fundamental difference between these two concepts. In simple terms, data refers to raw facts and figures, while insights are meaningful interpretations and […]
in this post and this one I described a couple of nice examples of correlation vs. causation cognitive biases. There are litterally hundreds out there that can be added. By doing a little search i came across a few nice […]
When analyzing a dataset sometimes we are working with data that does not represent the reality but it’s the result of a seleciton. This means that the seleciton made before the analysis is already creating a data bias. For example […]
In one of my previus posts about cognitive biases I mentioned the Occam’s razor principle. When it comes to data insights this is sometimes a very useful principle to keep in mind because data does’nt give insights itself but we […]
“if you torture the data long enough, it will confess to anything”. Ronald H. Coase, British Economist When working with a big dataset it’s easy to fall into the confirmation bias. We are looking for some insights, and usually what […]
In Turin there is an ancient church named Santuario della Consolata (its full name is “Chiesa di Santa Maria della Consolazione”), it’s origin dates back to the XVII century. The interior is very rich, with gold inlays everywhere on the […]
So after reading the Bananas Diet post we are now familiar with the causality bias concept. Another example of causailty bias i came across a few years ago for the first time is the black car crashes one. Articles like […]
What does Bananas and Black cars have in common? why correlation does not imply causality?
What’s a data bias? Why one of the most common one is called “survivor bias”? what’s a romanic bridge? And what does it have to do with WWII allies planes?