I’m new to the forums and have been catching up on old threads that look interesting. I was reading this thread discussing data standards, and realized what seems a fundamental issue confronting QS, especially if it is to continue to grow: data literacy.
Broadly speaking, my impression is that people are data illiterate. (Even working with data frequently in a startup, I am still just learning to truly think about data. I hope.)
So let me pose this question: what is practical data literacy, and assuming it can be taught, how do we teach it?
What do you mean by data-literacy? If you mean the ability to read and understand data, then I think it’s the responsibility of the application developer to present the data in an easy to understand way without expecting the user to have a degree in statistics. Most people are not going to really understand standard deviation when you give them raw numbers, but the idea immediately clicks when you present it as a visualization.
It’s fair to put the burden of visualization on the application developer.
What I mean by data literacy is the ability to think critically about data that is presented and understand what is / is not true based on data. e.g. understanding biased data, basic statistical biases, etc. A degree in stats is certainly not required, but it seems that a certain level of fluency with data is going to be necessary going forward.