Here, I present a simple graphical tool in R for visual detection and statistical testing of a trend among group means, where the groups are (usually) quantiles. I argue this is a good tool for exploratory data analysis as it allows non-linear trends to be detected.
The Q Method is a mixed method that combines a survey of individuals with factor analysis to determine what distinct perspectives are embedded in a population. In a class on urban sustainability, I demonstrated how this method can be used to reveal students' diverse perspectives on issues about which we assume they mostly agree.
In working with linear fixed-effects panel models, I discovered that I had to develop goodness-of-fit tests and diagnostics on my own, as the libraries for working with these kinds of models haven't progressed that far yet.
Fine-grained customization of citation styles in LaTeX's default bibliography environment can be hard to achieve. Here, I'll describe an alternative to the standard bibliography environment that I found for style customization without sacrificing the raw power of LaTeX.
I experimented with Bayesian networks for land cover classification in the Detroit metro area using census data as predictors. An example of using Bayesian networks for land cover classification in R is presented with code samples.