Data analysis is one of the most under rated, but most important parts of data science/econometrics/statistics/whatever it is you do with data.
It’s not impressive when it’s done right because it’s like being impressed by a door handle: it is something that is both ubiquitous and obvious. But when you’re missing the doorhandles, you can’t open the door.
There are lots of guides to data analysis but fundamentally there is no one-size-fits-most approach that can be guaranteed to work for every data set. Data analysis is a series of open-ended questions to ask yourself.
If you’re new or coming to data science from a background that did not emphasise statistics or econometrics (or story telling with data in general), it can be hard to know which questions to ask.
I put together this guide to offer some insight into the kinds of questions I ask myself when examining my data for the first time. It’s not complete: work through this guide and you won’t have even started the analysis proper. This is just the first time you open your data, after all.
But by uncovering the answers to these questions, you’ll have a more efficient analysis process. You’ll also (hopefully) think of more questions to ask yourself.
Remember, this isn’t all the information you need to uncover: this is just a start! But hopefully it offers you a framework to think about your data the first time you open it. I’ll be back with some ideas for the second time you open your data later.