Uncertainty is ubiquitous in science, but scientific knowledge is often represented to the
public and in educational contexts as certain and immutable. This contrast can foster distrust …

As technological advances continue to shape the field of statistics, approaches to teaching
statistics have evolved to incorporate computer-based tools. To determine the types of …

As a result of the increased emphasis on mis-and over-use of p-values in scientific research
and the rise in popularity of Bayesian statistics, Bayesian education is becoming more …

We propose a semester-long Bayesian statistics course for undergraduate students with
calculus and probability background. We cultivate students' Bayesian thinking with Bayesian …

Probabilistic models such as logistic regression, Bayesian classification, neural networks,
and models for natural language processing, are increasingly more present in both …

Undergraduate Bayesian education is an area that has started getting attention lately. As
many educational innovations and articles are published and increasingly more teaching …

With computational advances, Bayesian modeling is becoming more accessible. But
because Bayesian thinking often differs from learners' previous statistics training, it can be …

Uncertainty is ubiquitous in science, but scientific understanding is often represented to the
public and in educational contexts as certain and immutable. Adding to this problem is that …

Providing students insights into both the frequentist and Bayesian inferential frameworks is
challenging as simple textual instructions or mathematical formulations do not capture the …

Most statistics undergraduate curricula provide only a brief introduction to Bayesian
inference. Furthermore, there is evidence that learners can fail to appreciate core concepts …