This paper describes ideas for teaching introductory statistics courses.
This paper describes ideas for teaching introductory statistics courses.
The present paper offers some ideas for student projects that can be used in the introductory statistics class.
This paper describes different ideas that key on most of the important topics of the introductory statistics course.
The nonparametric approach to elementary statistics advocated in this paper presents statistical ideas simply and straightforwardly without overwhelming the student with mathematical derivations.
This paper is based on our attempts to develop an inference course at Reading in which students learn about concepts primarily through project work.
When it became apparent that many practical problems could not be solved by the standard procedures, a developmental effort began which combined the conceptual power of a prediction model approach with the computational power of high speed computers. A series of short courses were developed to introduce researchers to the new capabilities brought about through the combination of effective application of regression models with computing techniques.
The laws to be introduced share some of the characteristics of two other laws discussed in the paper. They will help to throw light on a very widely-used approach to teaching statistics in tertiary institutions.
This paper describes the need for a shift in emphasis away from the development of operations as described by Leontiev, towards the provision of increased experience of statistical activity.
This paper is about teaching large service courses in introductory statistics, with particular reference to engineering students and science students not majoring in mathematics.
The attempt to structure a curriculum which balances professional demands with intellectual aspirations induces academic quarrels that ballots do not assuage. In what follows I will address these issues.