Presentation 15: An Introduction to Parameter Estimation

In this video lesson, we introduce the theoretical background behind the method of moments in detail and offer a conceptual overview for maximum likelihood estimation. We then illustrate how to estimate unknown parameters of the binomial, geometric, Poisson, and hypergeometric distributions. When estimating the population parameters of the hypergeometric distribution, we present the basic steps involved for the mark and recapture sampling methodology. Finally, we explore one example of estimating the mean and standard deviation parameters of the normal distribution. This video lesson supports the Probability and Statistics Core Learning Resource (CLR) (https://mathsciresearchlaunchpad.wordpress.com/probability-and-statistics/) at the Mathematical Science Research Launchpad.