Philip Dixon, Department of Statistics, ISU
Statistical thinking and statistical analysis are a crucial part of science. Traditional statistical methods, e.g. hypothesis tests and confidence intervals, are based on a frequentist philosophy. Over the last few years, more and more papers are using Bayesian ideas (posterior distributions, credible intervals and model probabilities). I’ll explain Bayes Theorem, the Bayesian approach to statistics, and my view of the advantages and disadvantages of Bayesian methods. These will be illustrated by recent work on the economics of soybean aphid control and trends in the number of mourning doves in the western US.