Literature Index

Significant efforts have been made to overhaul the introductory statistics courses by placing greater emphasis on statistical thinking and literacy and less on rules, methods and procedures. We advocate broadening and increasing this effort to all levels of students and, importantly, using topical, interesting, substantive problems that come from the actual practice of statistics. We want students to understand the thought process of the "masters" in context, seeing their choices, different approaches and explorations. Similar to Open Source software, we think it is vital that the work of the community of researchers is accessible to the community of educators so that students can experience statistical applications and learn how to approach analyses themselves. We describe a mechanism by which one can collect all aspects or fragments of an analysis or simulation into a "document" so that the computations and results are reproducible, reusable and amenable to extensions. These documents contain various pieces of information (e.g. text, code, data, exploration paths) and can be processed to create regular descriptive papers in various formats (e.g. PDF, HTML), as well as acting as a database of the analysis which we can explore in rich new ways. Researchers, instructors and readers can control the various steps in the processing and rendering of the document. For example, this type of document supports interactive components with which a student can easily control and alter the inputs to the computations in a semi-guided fashion, gradually delve deeper into the details, and go on to her own free-form analysis. Our implementation for this system is based on widely used and standardized frameworks and readily supports multiple and different programming languages. Also, it is highly extensible which allows adaptation and future developments.

In the past decade there has been a substantial increase in the number of introductory statistics courses taught at the undergraduate level. Many have argued successfully for the extensive use of writing in such courses in an attempt to highlight the interdisciplinary role of statistics and acknowledge that a good statistician must also be good at summarizing his or her analyses to nonstatisticians. This point was made by Radke-Sharpe, who went on to add that incorporating writing demands time, energy, and creativity, but that it is usually well worth the effort. This article discusses the efforts made by the authors to include writing in their courses, and some of the techniques that made the writing process painless and productive for both students and faculty.

It is important to develop children's mental images of numbers parallel to their acquisition of counting and calculating skills. This is achieved by various kinds of activities which reveal, in one way or the other, the underlying structures. In school mathematics numbers are closely connected with calculations, which are, in my opinion, too much emphasized. The emphasis should be shifted towards handling of numbers without calculations. The introduction of stem-and-leaf displays is a step towards that end. Being based on the fundamental idea of place value stem-and-leaf displays also help developing the children's understanding of number.

The availability of comprehensive population registries in Scandinavian countries has facilitated extensive work in epidemiology on associations between risk factors and disease. The area has attracted many statisticians with no previous training in epidemiology. Experience has shown that some statisticians find it difficult to adapt to the practical challenges of this work. Not only is a basic understanding required of the statistical methods involved, but a particular cautious attitude is needed in the interpretation of epidemiological data with inherent uncertainties. An ability to communicate efficiently with coworkers is also essential. Yet the statistician must frequently deal with issues of a biological nature, in addition to technical aspects of data processing. It is difficult to take all these requirements into account in the education of professional statisticians. It is argued that the components not directly connected with statistics should still be integrated into the statistical training of future professionals. If statistics courses include a sufficient amount of relevant data analytic work, the students will be exposed to many of the challenges experienced in epidemiology.