Abstract

This talk introduces several foundational issues in statistical analysis and modeling that underlie techniques used to analyze imaging data. I begin by describing the standard linear model, followed by extensions that accommodate non-Gaussian data (the Generalized Linear Model) and data in which observations are not independent.

Finally, I discuss the critical challenges of multiple hypothesis testing and model selection.