Let's face it, people drop out of programs. While that can be easy to manage operationally, it can present problems when you're analysing your results. The last thing you want is for your results to become skewed or rather diluted by the participants who began with you but didn't stick around until the end. Thankfully there's a way to accommodate that on Makerble. Let's dive in.
In this example we'll imagine a Coding Course with 3 participants at the start. 1 of them drops out. Here's how to manage that and ensure you have reliable results at the end.
And as you'll see, the filtering isn't limited to Distribution over Time, you'll also see that same criteria applied to the other charts shown on your Progress Board.
There you have it! Hopefully you won't have need to contend with dropouts, but if you do, now you know how to!
