Teaching elementary Bayesian statistics with real applications in science

University courses in elementary statistics are usually taught from a frequentist perspective. In this paper I suggest how such courses can be taught using a Bayesian approach, and I indicate why beginning students are well served by a Bayesian course. A principal focus of any good elementary course is the application of statistics to real and important scientific problems. The Bayesian approach fits neatly with a scientific focus. Bayesians take a larger view, and one not limited to data analysis. In particular, the Bayesian approach is subjective, and requires assessing prior probabilities. This requirement forces users to relate current experimental evidence to other available information-including previous experiments of a related nature, where ''related'' is judged subjectively. I discuss difficulties faced by instructors and students in elementary Bayesian courses, and provide a sample syllabus for an elementary Bayesian course.