Abstract
The aim of a business statistics course should be to help students think statistically and to interpret and understand data, rather than to focus on mathematical detail and computation. To achieve this students must be thoroughly involved in the learning process, and encouraged to discover for themselves the meaning, importance and relevance of statistical concepts. In this paper we advocate the use of experiments and demonstrations as aids to achieving these goals. A number of demonstrations are given which can be used to illustrate and explain some key statistical ideas.
Highlights
There is a growing recognition that we need to change the way we teach business statistics
In the overview to the first conference Easton, Roberts and Tiao [1] note that there is “substantial dissatisfaction with much of current teaching of business statistics, especially as reflected in the poor selection of topics in popular textbooks and the limited opportunity for students to work with real data or to make serious use of statistical computing.”
We shall describe below demonstrations that we use in our business statistics course
Summary
There is a growing recognition that we need to change the way we teach business statistics. We identify three learning concepts found to be useful in helping business students appreciate the importance and value of statistics. As with any difficult subject, students learn statistical principles more effectively by active involvement in the learning process. This type of involvement is not uncommon in short courses presented to shop floor workers, supervisors and managers. Sowey [6] and Scheaffer et al [5] provide a number of activities that can be used in the classroom The aim of both experiments and demonstrations is to enrich learning by creating a different form of classroom activity, and to encourage participation in order to promote understanding and retention. Demonstrations are often computer-based, and with a little thought and ingenuity it is possible to create meaningful demonstrations for almost any topic that is taught in a statistics course
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