A Data-Oriented, Active Learning, Post-Calculus Introduction to Statistical Concepts, Methods, and Theory

This project is funded by the Course, Curriculum, and Laboratory Improvement program of the National Science Foundation. The three-year project, grant award #DUE-9950476, began on June 1, 1999.

Principal Investigators:

Allan Rossman, Dickinson College

Beth Chance, Cal Poly- San Luis Obispo

Karla Ballman, Mayo Clinic

Preliminary Content Outline and Paper:

Click here to see a preliminary course outline and here to see the paper that we have written for presentation at the 2000 Joint Statistical Meetings.

Project Overview:

We propose to develop curricular materials for a two-course sequence that introduces students at the post-calculus level to statistical concepts, methods, and theory. These courses will provide a more balanced introduction to the discipline of statistics than the standard sequence in probability and mathematical statistics. The materials will 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.

The introductory course differs from those for students not majoring in these fields by utilizing students' calculus knowledge and mathematical abilities to explore some of the mathematical framework underlying statistical concepts and methods. Distinguishing the second course from a traditional mathematical statistics course is the use of simulation, computer graphics, and genuine problems and data to motive and illustrate statistical theory.

The student audience targeted by this project is particularly important because it has been overlooked by previous curricular reform projects focused on the introductory course for students with majors outside of mathematics. Specifically, the proposed introductory course directly addresses the recommendation of the Mathematical Association of America that a data-oriented course be taken by every mathematics major. Also, a significant number of mathematics majors become statisticians and many become teachers of statistics. The proposed two-course sequence introduces these students to content and pedagogy which prepares them well for careers in statistics or teaching.

In addition to developing, testing and revising these materials, the project includes a significant program of dissemination and evaluation. During the first year of the 27-month project, the principal investigators will write a complete set of materials for the courses while class-testing the introductory materials at the University of the Pacific and the statistical theory materials at Macalester College. The second year consists of further revising and class-testing at Dickinson College as well as UOP and Macalester. During the final summer of the project, the principal investigators will conduct a week-long faculty development workshop to enable instructors from a variety of institution types around the country to use the curricular materials in similar courses at their institutions. Also, the materials will be prepared for commercial publication at this time.

The primary outcome expected of this project is two fully self-contained textbook/workbooks which integrate investigative activities with more traditional exposition. Other expected outcomes include a suite of Java applets designed to aid students' conceptual visualization and extensive support materials such as instructor's guides and sample examinations. A final anticipated outcome is the faculty development workshop.