A Master’s Class: A Return to Form

It’s been well over a year now since I’ve written here. It’s been a busy year, chock full of new places, new people, and of course new ideas. Also food. Lots of food. But we’ll get to that if we have time later on. For those unaware, I spent the past year in Scotland, earning my Master’s in Quantitative Methods in Biodiversity, Conservation, and Epidemiology (yeah I know, it’s a hell of a name) from the University of Glasgow.  Which, incidentally, is why I’m here again, writing.

The University of Glasgow, where I spent last year, learning the fanciest of ways to count animals. Image source: http://en.wikipedia.org

This the first in what will hopefully be a fairly respectable number of posts discussing my Master’s project. These posts will range from fairly basic explanations of what I did and why I did it to far more technical discussions of statistics and modelling as well as posts covering the fundamentals of genetics and ecology. The goal is to create a body of articles broad enough that most anybody could, in theory at least, wander along and learn everything they need to know to understand my work, regardless of their background. As with most theories, its tough to say how accurate that one is going to be, but I guess we’ll see now won’t we?

A few things to start off with, just so we’re clear. I am going to be citing a lot of Wikipedia. Don’t get me wrong, for the technical stuff you’ll still get plenty of scholarly articles explaining model structure for Bayesian inference or the merits of different measures of relative genetic distance, but for some things (like explaining probability density functions or background on Rana temporaria), I have yet to find a more accessible or complete resource as a well-constructed Wikipedia page. That may not be the most academic thing in the world, but this isn’t the most academic blog in the world, and that’s probably an okay thing.

I will probably make jokes. I don’t promise to, but I don’t promise not to either. They will probably be terrible, as many science-based jokes are. You’ll have to live with that.

There will be posts unrelated to my work. If I come across some new article I find particularly interesting, I will most likely write about it. I will also probably talk about books. I tend to do that a lot, so you’ve been warned.

I’m not entirely sure how to end this, so I’ll just say hi and welcome back. Hope you learn something.


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