  This article, produced as a result of the Symposium on Statistical Inference,
is an introduction to the literature on the function of expertise, judgment,
and choice in the practice of statistics and scientific research. In
particular, expert judgment plays a critical role in conducting Frequentist
hypothesis tests and Bayesian models, especially in selection of appropriate
prior distributions for model parameters. The subtlety of interpreting results
is also discussed. Finally, external recommendations are collected for how to
more effectively encourage proper use of judgment in statistics. The paper
synthesizes the literature for the purpose of creating a single reference and
inciting more productive discussions on how to improve the future of statistics
and science.
