By Krista Varanyak, The University of Virginia
The introductory regression course is often the first exposure that statistics majors have to experience the versatility of statistics across disciplines. Therefore, it is pivotal to spark interest and develop fundamental analytical skills in this course, if the intention is to produce statisticians upon graduation. One way we have found to do this in a medium enrollment (~60), intermediate level regression course is through a final project-based assessment where groups are expected to learn a concept that was not covered in the course; analyze a data set; and present their findings. The project discussed by this poster stresses the importance of evaluating evidence to undergraduate statistics majors through real world applications. Through the class project students learn to reason about new inference techniques, to face intricacies of “real data”, to interpret their results in context, and to evaluate limitations of their chosen technique. Students were able to exceed expectations and to demonstrate genuine understanding of skills required of statisticians: collaboration, communication, and accurate statistical analyses. Feedback from the students was overwhelmingly positive and showed they enjoyed the real-world application of their new knowledge. This poster will discuss the project in depth: including project guidelines, how to manage group work in this particular setting, example student submissions, student feedback, and identify areas for improvement.