There are few things I enjoy more than when someone takes the time to clearly communicate a complex idea. The whole “you don’t know it until you teach it” phenomenon gives me the utmost respect for those who put effort into bridging the gap to us non-experts. Oftentimes, the clearest way to communicate something complex is visually, and I want to share a cool example with you:
Eigenvectors and eigenvalues: explained visually by Victor Powell and Lewis Lehe
We use eigenvector-based linear algebra for a multitude of analyses in molecular ecology, from the types of clustering analyses offered by adegenet (PCA, CCA, DPCA, YMCA?, ASPCA?) to the estimation of phylogenetic signal. If you stared as hopelessly as I did at the chalk board during undergraduate math courses, learning what the heck an eigenvalue is could have been an uphill battle. If only I would have had these arrows to move around!
Bonus: you can also check out modules on Principal Components and Markov Chains! I know you can’t resist a good Markov Chain.