In this paper, I provide a tutorial exposition on maximum likelihood estimation (MLE). The intended audience of this tutorial are
researchers who practice mathematical modeling of cognition but are unfamiliar with the estimation method. Unlike least-squares
estimation which is primarily a descriptive tool, MLE is a preferred method of parameter estimation in statistics and is an
indispensable tool for many statistical modeling techniques, in particular in non-linear modeling with non-normal data. The purpose
of this paper is to provide a good conceptual explanation of the method with illustrative examples so the reader can have a grasp of
some of the basic principles.