p < 0.05.
How many of you have seen these 6 little characters and felt The Rush? Admit it--it's better than Christmas morning, your first kiss*, and good bourbon all rolled into one! You want to run through the halls of your Classy Institution screaming, "I HAVE DATAAAAAAAA!!!!" - and you very well might do that.
But here's the thing we often forget: p > 0.05 is data, too. And having more significant differences doesn't necessarily mean your paper's going to a fancier journal. Earlier this evening, I caught whiff of a conversation on twitter, started by Sciencegurl, and it made me a little sad. She tweeted:
When the kind folks of twitter asked her what happened, she responded:
And that just about broke my heart. PIs, do you understand that negative data might not be the result of your trainees being bad at science, but instead perhaps there simply are no differences?
Here in the Laboratory of Neuroscience and Awesomeness, we are getting to the point where we've collected what can only be described as a shit ton of data, and it is my job as PI to help my trainees make sense of it all. Their natural inclination is to hope that experimental and control groups are different in every measure possible, but that is of course not how things pan out, ever. For example, we recently had some interesting behavioral data, and so I asked one of my grad students to process tissue from the brains of the animals from that study (to me, running a behavioral experiment without looking at the brains in some capacity is like roasting a chicken and then throwing out the bones without making a stock. So much potential goodness to squeeze out!) So grad student worked extremely hard to do this --she worked long hours, all through winter break, and well into this semester. She trouble shot, she took gorgeous images, and she handed me a spreadsheet full of raw data that I analyzed in every way I could think of, from every angle imaginable. But no matter how much I squinted or turned my head sideways, there were simply no significant differences between groups.
Would it have been fun if we had found differences? Of course. Does the fact that this data set happened to turn out negative mean we won't include it when we write it up? Fuck no. Like it or not, these data are part of our narrative, and it's our job as scientists to think hard about what both positive AND negative data mean for the story we're trying to tell. Not everything may fall perfectly into place the way we'd originally imagined it, but half the fun of being a scientist is trying to wrap your brain around the data you have, and coming up with a new interpretation of what's going on. Don't let your data make you sad, and for fuck's sake don't take it out on your trainees--make your data work for you. Because after all, the data are what the data are.
* truth be told, my first kiss was not all that pleasant, because braces.