I recently decided to create two blogs as outlets for my research. The first (The Richness of Life) focuses more on the organisms I work with as an ecologist and my general interest as a student of natural history. This blog on Quantitative Ecology stems from my recent obsessive frustration with analyzing various data sets. I have a decent background in the design of ecological experiments but have recently been trying to increase my statistical fluency (see Ellison and Dennis 2010 – Frontiers in Ecology and the Environment). While searching for information on coding in R and WinBUGS, I have utilized a variety of sources including forums and blogs where people have shared their experiences and deciphered cryptic error messages. I also came across two articles on the benefits of blogging as an academic (here and here). Without duplicating everything they wrote, I’ll say that my desire to blog about my research comes from a few different perspectives. First, this is what I spend my time thinking about and it’s nice to share it with like-minded individuals. Second, I hope that this could contribute to fun and productive collaborations. Third, I hope to help people on their own (sometimes painful) journeys in the realm of experimental design and analysis (including statistics and inference). Finally, I believe it will help me as a teacher if I practice articulating my thoughts and questions on these complex subjects.

I will start this first blog with a recommendation of one of my favorite books on data analysis that I’ve come across. Introduction to WinBUGS for Ecologists: Bayesian approach to regression, ANOVA, mixed models and related analyses is an exceptional book for self-teaching and offers a nice introduction to using WinBUGS for analyzing ecological data in a Bayesian framework.

http://rcm.amazon.com/e/cm?lt1=_blank&bc1=000000&IS2=1&bg1=FFFFFF&fc1=000000&lc1=0000FF&t=run00e-20&o=1&p=8&l=as1&m=amazon&f=ifr&md=10FE9736YVPPT7A0FBG2&asins=0123786053

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I figured that I can't leave you hanging as a lonely nerd so I would come out and hang with you. I hope you don't mind. While I have to admit that I am not familiar with the types of statistical analysis that are probably common in your field, your post did leave me intrigued. After a quick Google search on WinBUGS I was surprised to learn that the "G" in the name pays tribute to one J. Willard Gibbs who is near and dear to my heart. In his time he published a series of papers that I would argue makes up more than half of the undergraduate chemistry curriculum. His work in the field focused on the answering whether or not a chemical reaction will occur and, if it does, to what extent it occurs. His work was based almost entirely on thermodynamics. I am not sure exactly how all of the history fits into the equation (and if Gibbs even had anything to do with it) but, as it turns out, most of Gibbs' work can be formulated by calculating averages of large ensembles of particles. Every thermodynamic quantity that we could ever think to measure (e.g. pressure, temperature, enthalpy, etc.) can be obtained by determining ensemble averages! When this idea is combined with quantum mechanics it becomes possible to calculate everything we would ever want to know about chemistry and, in turn, biochemistry, biology, ecology, psychology! Unfortunately, the equations are far too complex to be solved exactly and we end up unable to apply the ideas to all but the simplest of situations. Fortunately we have other scientists (like ecologists!) who can make their own approximations and make sense of the many important problems we wish to solve. In any case, I always find it fascinating that some of the tools we develop can be used over such a wide variety of disciplines. Even all the way from thermal physics to ecology.

Despite all of the gin I'd had, I remember you talking about the importance of Gibbs Free Energy at Coby's wedding. I had no idea that Gibbs sampling was named after the same Gibbs. In a brief search, I couldn't find why it was named after him. I may see if I can find the original article to see if it offers an explanation. I wouldn't be surprised if we use a lot of the same models and statistics. It seems like a lot of the statistical models we use were developed by physicists (although maybe not the Gibbs sampler).Anyway, thanks for the nerd camaraderie!

I'm on board!