I had a great meeting with my second supervisor yesterday. I think retired life agrees with her – she was in a better mood than I’d ever seen her in before.

We talked about my analysis together, talked stats, went through the calculations I’d made. It turns out my stats are right, but it’s difficult to justify why the effects I’ve found should be of theoretical interest. My supervisor asked if I’d looked at some of my other variables instead – ones I had originally been interested in, but didn’t bother exploring very much because the nature of the data didn’t fit the tests I could do and, more importantly, it didn’t occur to me that there could be a way to change the nature of the data. Of course, it turns out there is, and now, thanks to her, I know how to do it.

I love talking about statistics. The philosophy of statistics is bizarre, ironic, and contradictory. Statistics can be mind-blowing – just when you think you have the answer, it escapes you. There are strengths and weaknesses, advantages and disadvantages, pros and cons to everything. There are assumptions and conditions in which you can violate assumptions. There are multiple ways of doing the same thing, and multiple ways of deciding which way to do it. I still have the undergraduate reflex of flinching when I see a significant p value, but I have matured enough to put my excitement to one side and check other indicators of significance, and dilute my enthusiasm with caution for sample sizes, skewed distributions, and Type I errors.

For all her coldness, I have a great second supervisor. She knows her stuff, and she likes it when you share her passion for stats. We had some great ideas, and she showed me how to do things I hadn’t even thought about before. My final study was going to go in some bizarre, barely-justfiable direction I wasn’t even sure I was interested in, simply because that was the only area in which I could find results worth reporting. Now I see results worth reporting aren’t merely the significant ones – they’re the ones that spark theoretical interest. I’m not going to do what I thought I had to do – I’m going to go back to what I was originally interested in, and reanalyse that data. I didn’t find much of interest in it the first time round, but, thanks to my supervisor, and the beauty of stats, I find there are things in my data worth talking about.


This is a great feeling.

I’m in the game again! Maybe I’ll even get my head around this thing!