Another vital thing to do is to have a clear idea of our predictor and response variables before we even start the experiment. Before we ever put a mouse in a testing box or a seed in a growth chamber, we should identify what we’ll measure.

Hopefully, if we know our study system well or perhaps have some preliminary data, in that case, we can estimate what the data will look like, which allows us to think about and plan for the type of analyses we’ll carry out. Maybe that sounds like wishful thinking, but this whole course is about the importance of knowing what data looks like.

Get hands-on with 1400+ tech skills courses.