Abstract
As powerful software and large real-world data sets have entered the mainstream college classroom, and statistics has entered the K-12 classroom, university faculty have been slowly modifying "introductory stats" courses to emphasize statistical reasoning and discovery. JMP has clearly played a role in facilitating and adapting with these modifications. This talk reviews nine specific ways that JMP can be instrumental in redefining what we regard as fundamental and introductory topics, and argues that the structure and approach of JMP can shift traditional boundaries between introductory and more advanced topics. The software's native features – such as Graph Builder's visualizations, simulation, seamless integration of parametric and nonparametric tests, painless logistic regression, bootstrap CIs, sampling weights and intuitive data management tools – allow us to re-imagine the intro course, inspire undergrads to pursue further study in analytics, and provide value to analytically oriented firms. The presentation will include some classroom-tested demonstrations of "advanced" topics, couched in a way that introductory students can grasp them. Additionally audience members will be invited to share their insights about skills, concepts and orientations that they seek in entry-level employees fresh out of college.