In my last post I lamented the fact that there is too little focus on data thinking in data science and data visualization, and I described how much of a struggle it’s been for me to figure out how to learn and teach these skills. When I teach my academic visualization course, the thing the most exemplifies this need is the way I struggle to teach how to formulate good
The problem itself, as it is framed here, is kind of out of focus. The correct question usually arrives thousands of hours after you started looking into the data. And, in order to get the right questions you need to:
I do not disagree with you. The right questions typically come after you engage with the data for an extensive time period. This is why the focus here is on asking questions the right way rather than asking the right questions. There is a lot to say about how the questions become better and better over time.
The problem itself, as it is framed here, is kind of out of focus. The correct question usually arrives thousands of hours after you started looking into the data. And, in order to get the right questions you need to:
- have domain-specific knowledge
- a sound statistical background
That is it.
I do not disagree with you. The right questions typically come after you engage with the data for an extensive time period. This is why the focus here is on asking questions the right way rather than asking the right questions. There is a lot to say about how the questions become better and better over time.