A Data-Oriented, Active Learning, Post-Calculus Introduction to Statistics


Authors: 
Rossman, A., Chance, B., Ballman, K.
Year: 
2000
Publisher: 
Joint Statistical Meetings, August
Abstract: 

We describe this NSF-funded project to develop a two-course sequence that introduces post-calculus students to statistcal concepts, methods, and theory. These courses provide a more balanced introduction to the discipline of statistics than the standard sequence in probability and mathematical statistics. The materials incorporate many features of successful statistics education projects that target less mathematically prepared students. Such features include developing students' conceptual understanding of fundamental ideas, promoting student explorations through hands-on activities, analyzing genuine data drawn from a variety of fields of application, and integrating computer tools both to enhance students' learning and to analyze data efficiently. Our proposed introductory course differes by utilizing students' calculus knowledge and mathematical abilities to explore some of the mathematical framework underlying statistical concepts and methods. Distinguishing the second course is the use of simulation, computer graphics, and genuine problems and data to motivate and illustrate statistical theory. In this presentation, we outline the goals, content, and pedagogy of this sequence. We also present examples of student activities from both courses.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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