As a way to engage all of the students who pass through our classes, the CURV database profiles statisticians and data scientists with backgrounds that aren't typically seen in our textbooks and histories. With dozens of accounts, you can use the database for a statistician-of-the day activity.

Celebrate the contributions of people year round with "awareness" months. This document gives you a starting point for months where you can share the contributions of people who may not look like the students in your class. For example, Amstat.org regularly interviews statisticians for Black History Month and Women's History Month.

Engaging and motivating students in undergraduate statistics courses can be enhanced by using topical peer-reviewed publications for analyses as part of course assignments. Given the popularity of on-campus therapy dog stress-reduction programs, this topic fosters buy-in from students whilst providing information regarding the importance of mental health and well-being as it impacts learning. This paper describes how instructors can use a study on the benefits of human–dog interactions to teach students about study design, data collection and ethics, and hypothesis testing. The data and research questions are accessible to students without requiring detailed subject-area knowledge. Students can think carefully about how to collect and analyze data from a randomized controlled trial with two-sample hypothesis tests. Instructors can use these data for short in-class examples or longer assignments and assessments, and throughout this article, we suggest activities and discussion questions.

Dr. Rochelle Gutierrez (2002) stated "equity is ultimately about the distribution of power - power in the classroom, power in future schooling, power in one's everyday life, and power in a global society." This presentation unpacks ways in which statistics classrooms can put power in students' hands. 

Our recent research focuses on integrating Culturally Relevant Data into statistics and data science education. We’ve developed methods that connect coursework directly to students’ lived experiences, significantly enhancing engagement and understanding, particularly for those from historically marginalized groups. Our approach bridges the gap between theoretical data science and real-world application, making learning both accessible and impactful. Initial results from pilot courses are promising, and we are excited about the potential to further transform how data science is taught. Join us in making data science education more inclusive and effective for everyone