Sorry, you need to enable JavaScript to visit this website.

Simulation-based inference after Stat 101

Presented by:

Nathan Tintle (Dordt College) & Beth Chance (Cal Poly San Luis Obispo)


The use of simulation-based methods for helping students understand (and be able to explain!) the reasoning of statistical inference is growing in popularity for the Stat 101 course. In this breakout session, we will discuss ways that we can leverage the benefits of simulation-based inference in courses after Stat 101. We will discuss how simulation-based inference may be useful in discussing more advanced topics like power, blocking, choice of statistic and more. Part of the session will include time for participants to weigh in on questions about the potential role of simulation-based inference in courses after Stat 101.


(Tip: click the fullscreen control)

Having trouble viewing? Try: Download (.mp4)

(Tip: right-click and choose "Save As...")

Teaching with Simulation-Based Inference