Multivariate Statistics or: How I learned to stop limiting my analyses and love n-dimensionality, matrix algebra, and R

Or, at least, that’s what I’d like the title to be at the end of this semester. I’m auditing a multivariate statistics course this semester, and am really enjoying it!

My initial reason was that I was tired of looking at PCA plots and only being able to say, “Okay, since these points are closer together, they are more similar, and the first two principle components explain 67% of the variation,” without knowing what assumptions went into the analyses, what they mean in the “real world”, or being able to critically evaluate the work of others. A few weeks in, though, I’ve already learned a lot, starting with applied matrix/linear algebra. Sometimes, working and thinking in more than 3 dimensions feels a bit like a Magic Eye image, where you just need to sort of relax your senses to perceive what’s there. I feel like I am finally becoming proficient in R, which I’ve been working toward for a while. Most excitingly, our term project is to analyze a dataset, and I’ve been discussing with my minor advisor how I could use this as an opportunity to work up some data that he has on microbial communities in desert soil crusts. Fun!

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