  The use of simulation-based methods for introducing inference is growing in
popularity for the Stat 101 course, due in part to increasing evidence of the
methods ability to improve students' statistical thinking. This impact comes
from simulation-based methods (a) clearly presenting the overarching logic of
inference, (b) strengthening ties between statistics and probability or
mathematical concepts, (c) encouraging a focus on the entire research process,
(d) facilitating student thinking about advanced statistical concepts, (e)
allowing more time to explore, do, and talk about real research and messy data,
and (f) acting as a firmer foundation on which to build statistical intuition.
Thus, we argue that simulation-based inference should be an entry point to an
undergraduate statistics program for all students, and that simulation-based
inference should be used throughout all undergraduate statistics courses. In
order to achieve this goal and fully recognize the benefits of simulation-based
inference on the undergraduate statistics program we will need to break free of
historical forces tying undergraduate statistics curricula to mathematics,
consider radical and innovative new pedagogical approaches in our courses,
fully implement assessment-driven content innovations, and embrace computation
throughout the curriculum.
