Teaching Tools for Statistics: Bootstrapping
With Prof. Tom Busey, I helped to develop statistical software for use in undergraduate research methods courses. Using bootstrapping, a methodology which is free from the typical assumptions about distributions that standard tools like analyses of variance (ANOVAs) employ, these tools help students understand the process of resampling from data to estimate t-values and correlations between datasets. The tools are available at Prof. Busey's website and include tools for tests involving conditions both within and between subjects, correlations, and interactions. These tools were implemented with the guidance of Prof. Busey and also Rick Hullinger.
Virtual EEG: Experiments from pre-recorded EEG data
Using a database of pre-recorded EEG data, this software allows students to create their own experiments by categorizing stimuli (images) of a variety of types (examples include faces; whole bodies; animals; low or high, positive negative emotional valence), plotting the data from multiple sources on the scalp, and computing statistical analyses of difference between the chosen categories. The software is available online here and was published in the Journal of Undergraduate Neuroscience Education. This version of the software was created from an initial web-based framework and data from the lab of Prof. Tom Busey, with guidance from Ben Miller.