Introductory Statistics through Resampling: Addressing the Reproducibility Crisis in the Sciences

Application Form

To apply, please follow the link above and fill out the form, where you will be asked to submit the following:

• 1. Your Curriculum Vitae.
• 2. A statement of purpose describing why you want to join the workshop and what you hope to get out of this.

*Limited funding is available for applicants who apply by April 15th.

Space and funding are limited.

This workshop takes up the reproducibility crisis documented in psychology, biomedicine, economics, and related sciences and treats it as an opportunity for statistics education rather than a shortcoming of practicing scientists. We will explore what the reproducibility crisis is in these fields and why it matters for scientific knowledge production. We will discuss connections between the widely reported replication failures and standard ways introductory statistics is taught.

Using Understanding Data: A 21st Century Approach to Statistics and Data Science, the workshop introduces resampling as a core inferential method for reasoning about variability, uncertainty, and evidence. Participants will work through selected concepts and problems from the textbook and examine instructional choices involved in teaching a resampling-based introductory course. Time is reserved for focused discussion and expert consultation on adapting the curriculum to participants’ home institutions, including pacing, assessment, and local program constraints.

Organizers

• Amanda Beacher (COMAP)
• Jennifer A. Czocher (Texas State)
• Eric J. Deeds (UCLA)
• Alan Garfinkel (UCLA)
• Brendan Kelly (Harvard)