Experiencing a Paradigm Shift: Teaching Statistics Through Simulation-Based Inference

Document Type

Conference Proceeding

Publication Date



Mathematics, Statistics, and Computer Science


statistics, similation methods, college teaching, inference


For decades, introductory statistics has been taught as an application of formulas, making use of normal and other distributions, and relying heavily on algebraic skills of students, in short, emphasizing mathematical thinking. More recently, several textbook author teams have published statistics textbooks that place an increased emphasis on simulation and randomization methods as the way to motivate statistical reasoning (e.g., inference) leading to a decreased emphasis on the algebraic manipulation of formulas and theory-based approximations to sampling distributions (e.g., [3]; [7]). This paper describes simulation-based inference curricula more fully, reports on the necessary steps towards the implementation of such an approach, and provides both qualitative and quantitative comparisons of this new pedagogical approach with a more traditional approach. Appropriate justification of the approach to teaching and learning statistics is also provided, along with providing an overview of recent trends to shift to this approach in statistics courses taught at the high school, junior college, and university levels across North America, including a number of Christian colleges and universities affiliated with the ACMS.


Paper presented at the ACMS (Association of Christians in the Mathematical Sciences) Biennial conference held in Ancaster, Ontario, in May 2015.

Source Publication Title

Proceedings of the Twentieth Conference of the Association of Christians in the Mathematical Sciences


Association of Christians in the Mathematical Sciences

First Page