Volume 3, Number 1 (March 1995) ISSN: 1069-1898
Jon E. Anderson and J. David Dayton, "Instructional Regression Modules Using XLISP-STAT" (37K)
XLISP-STAT is free statistical software available for a variety of computing platforms. This article presents XLISP-STAT programs and explanations for three kinds of educational modules relevant to an applied regression course: new mouse modes, regression surface displays, and dynamic simulations for the sampling distribution of an estimated regression coefficient. These modules can be incorporated into laboratory sessions or lectures to demonstrate topics like case diagnostics, visualizing multiple regression, and the impact of distributional assumptions on the sampling distribution of an estimated regression coefficient. The structure of the modules can be easily modified by instructors to include additional topics. --JEA
Key Words: Influence diagnostics; Dynamic graphics; Dynamic simulation.
Clifford Konold, "Issues in Assessing Conceptual Understanding in Probability and Statistics" (27K)
Research has shown that adults have intuitions about probability and statistics that, in many cases, are at odds with accepted theory. The existence of these strongly- held ideas may explain, in part, why learning probability and statistics is especially problematic. One objective of introductory instruction ought to be to help students replace these informal conceptions with more normative ones. Based on this research, items are currently being developed to assess conceptual understanding before and after instruction. --CK
Key Words: Instruction; Pre-post testing; Student intuitions.
Kieran Mathieson, David P. Doane, and Ronald L. Tracy, "A Program for Visualizing Comparisons Between Two Normal Distributions" (23K)
This paper describes one program in the Teaching Statistics Visually (TSV) project. TSV supports inductive learning in introductory undergraduate applied statistics courses. The program (1) helps teach concepts rather than analyze data, (2) focuses on one module in a statistics course, (3) relies on visualization rather than formulas, (4) is easy to use, (5) is flexible, supporting different learning levels, and (6) is easy to manage, requiring commonly available resources and incorporating special features to simplify classroom use. A prototype version of the program "Comparing Two Normal Distributions" is included with this paper. The reader is invited to experiment with the program and to send comments and suggestions for improvement to the authors. --KM
Key Words: Statistics education; Computer-assisted instruction; Animation; Color graphics; Windows.
R. Romero, A. Ferrer, C. Capilla, L. Zunica, S. Balasch, V. Serra, and R. Alcover, "Teaching Statistics to Engineers: An Innovative Pedagogical Experience" (33K)
In recent years, the growing consciousness of the importance of statistics in the training of engineers has been accompanied in the western world by an increasing dissatisfaction with the teaching of statistics in universities. Within the framework of the Educational Innovation Project (PIE) of the Polytechnic University of Valencia, a group of teachers in the Department of Statistics introduced an innovation project beginning in 1989. This project has entailed a complete restructuring of the syllabus, as well as the teaching methodology. In this paper we explain different aspects of this project, emphasizing the important role of computer resources and the satisfactory results obtained. --RR
Key Words: Statistics education; Total Quality University; Educational quality improvement; Active learning.
Teaching Bits: A Resource for Teachers of Statistics (34K)
This column features "bits" of information sampled from a variety of sources that may be of interest to teachers of statistics. Joan Garfield abstracts information from the literature on teaching and learning statistics, while Laurie Snell summarizes articles from the news and other media that may be used with students to provoke discussions or serve as a basis for classroom activities or student projects. --JG
David A. Dickey and J. Tim Arnold, "Teaching Statistics with Data of Historic Significance: Galileo's Gravity and Motion Experiments" (20K)
This article demonstrates the use of two datasets as an aid in teaching polynomial and nonlinear regression. The data were gathered by Galileo during his studies of falling bodies and projectiles. In analyzing and discussing these data, students are challenged to give thought to parsimony, independent and dependent variables, and the importance of understanding the scientific nature of the experiment. The opportunities for class discussion are especially rich in this understandable and real experiment, particularly when coupled with graphical analysis. --DAD
Key Words: Galileo; Polynomial regression; Ockham's razor; Nonlinear regression.
Editorial Board for Volume 3, Number 1
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