I would like to show you an effective new approach to teaching the introductory statistics course. I have written three papers about the approach, the abstracts of which follow:
The Introductory Statistics Course:
Abstract: This paper proposes six concepts for discussion at the beginning of an introductory statistics course for students who are not majoring in statistics or mathematics. The concepts are (1) entities, (2) properties of entities, (3) variables, (4) a major goal of empirical research: to predict and control the values of variables, (5) relationships between variables as a key to prediction and control, and (6) statistical techniques for studying relationships between variables as a means to accurate prediction and control. After students have learned the six concepts they learn standard statistical topics in terms of the concepts. It is recommended that each concept be taught in a bottom-up fashion with emphasis on concrete practical examples. It is suggested that the approach gives students a lasting appreciation of the vital role of the field of statistics in empirical research.
This paper contains 31,000 words and 190 references and is available over the Internet in four formats:
The Entity-Property-Relationship Approach
Abstract: This paper introduces the "entity-property-relationship" approach to science and statistics at a level suitable for students in an introductory statistics course.
This paper contains 21,000 words (including 24 exercises) and is available over the Internet in Adobe Portable Document Format. (306 kilobytes. For information about the free Adobe PDF reader, click here. Click here if you have a problem viewing the PDF document.)
Eight Features of an Ideal Introductory Statistics Course
Abstract: This paper discusses the following features of the author's ideal introductory statistics course: (1) a clear statement of the goals of the course, (2) a careful discussion of the fundamental concept of 'variable', (3) a unification of statistical methods under the concept of a relationship between variables, (4) a characterization of hypothesis testing that is consistent with standard empirical research, (5) the use of practical examples, (6) the right mix of pedagogical techniques: lectures, readings, discussions, exercises, activities, group work, multimedia, (7) a proper choice of computational technology, and (8) a de-emphasis of less important topics such as univariate distributions, probability theory, and the mathematical theory of statistics. The appendices contain (a) recommendations for research to test different approaches to the introductory course and (b) discussion of thought-provoking criticisms of the recommended approach.
This paper contains 18,000 words and is available over the Internet in Adobe Portable Document Format (158 kilobytes. For information about the free Adobe PDF reader, click here. Click here if you have a problem viewing the PDF document.)
I welcome your comments about the ideas, either in the e-mail list EdStat-L (= the sci.stat.edu Usenet newsgroup) or via e-mail.
Thank you for your interest.
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