Statistics is our passion

A data-driven, project-based introductory curriculum for everyone

Quantitative Analysis Center

222 Church Street – Wesleyan University

Middletown, CT 06459

Lisa Dierker – ldierker@wesleyan.edu | LinkedIn

SUPPORTING DATA-DRIVEN PROJECTS ACROSS DIFFERENT SOFTWARE ENVIRONMENTS

SAS R PYTHON Stata SPSS

The curriculum supports students to work with existing data covering psychology, health, business, government, education, environmental science, biology and more. From existing data, you’ll be able to pose questions of interest to you and then use statistical software (e.g. SAS, R, Python, Stata or SPSS) to turn raw data into useful information.

Statistical analysis is arguably the most salient point of intersection among diverse disciplines, yet developing analytic skills is often viewed as an obstacle rather than an opportunity to pursue your own interests and to answer questions that you feel passionately about.

This is why we created Passion-Driven Statistics. It is statistics in the service of your own research – in the service of your passion. It is a multidisciplinary, project-based curriculum that supports students in conducting original research, asking original questions, and communicating methods and results using the language of statistics.

This website presents learning materials to support this innovative, project-based approach and to directly and creatively tackle many of the most significant challenges currently faced by instructors and students. We believe that students from diverse educational, social and economic backgrounds deserve not only a seat in a classroom, but also a welcoming place at the table. Our goal is to increase the number and diversity of students exposed to meaningful and empowering data analysis experiences and to inspire the pursuit of advanced data-driven experiences and opportunities for everyone! Anyone interested in teaching or learning statistics will find the site useful.

OUR PARTNERS

FUNDING

The development of this course and supporting instructional materials was supported by grant #0942246, #1323084, and #1820766 from the National Science Foundation, Improving Undergraduate STEM Education (IUSE).