ABSTRACT

Mathematical Sciences (21)

The project is developing two post-calculus statistics courses for science, technology, and mathematics students that are designed to provide a solid introduction to the intellectual content and broad applicability of statistics as a discipline while respecting the strong quantitative backgrounds of the students who take these courses. Both courses contain investigative laboratory modules (labs) that emphasize the process of science and data analysis relevant for science and social science students. Much of the material in the 1st course is being adapted from DUE-9950476 "A Data-Oriented, Active Learning, Post-Calculus Introduction to Statistical Concepts, Methods, and Theory" (ISCAT). The 2nd course extends ISCAT and utilizes integrative research-based lab methodology currently used in science courses at Grinnell College (partially funded by DUE-9950289). Labs in both courses are being developed so that they can be individually integrated into many courses in both undergraduate statistics and other disciplines.

The intellectual merit of this project is to contribute to the scholarship of statistics education by developing material that expands the successful reforms of the algebra-based introductory statistics course and inquiry-based science courses into early statistics courses designed for students with strong quantitative skills and interests. This collaborative project aims to deepen the statistical knowledge of undergraduates who are future scientists and quantitative social scientists in order to strengthen the interdisciplinary dialog between statisticians and scientific investigators in the future. The project also addresses a 2004 CUPM Guide recommendation by developing a series of labs that emphasize data analysis and encourage students to collect data, determine an appropriate technique for analysis, use technology, perform the analysis, make inference, interpret and then present the results.

The broader impacts of the project include creation of models for mathematics, technology and science students to develop interdisciplinary data analysis and research skills by creating a 2nd course in statistics that easily fits into existing curricula at many institutions. This allows institutions that may not be able to add new courses to their curriculum to incorporate a few labs into a standard probability course or other science courses, thereby increasing the quantitative skills of students majoring in other disciplines. The development of the laboratory modules brings together information across many disciplines and increases collaboration between faculty in the physical, biological and social sciences. This material is being disseminated through presentations at professional meetings, by publication in statistics education journals, and online at CAUSEweb (#DUE-0333672). As modeled by ISCAT, dissemination of these labs includes data and simulations that are accessible through a variety of data analysis tools such as Excel, Minitab, Stata, R, and java applets on the internet.

Please report errors in award information by writing to: awardsearch@nsf.gov.