Literature Index

A novel assignment exercise is described, in which students use a dictionary to estimate the size of their vocabulary. This task was developed for an introductory statistics service course, although it can be modified for use in survey sampling courses. The exercise can be used to simultaneously assess a range of core statistics skills: sample size estimation, obtaining a simple random sample, estimating a sample proportion, measuring the sample error of this proportion, and similarly for a scalar multiple of a proportion. The outcome of this exercise involves the student discovering something about themself, which serves as a natural motivator and a tool for generating interest in the discipline of statistics.

Owing to the shortage of didactic preparation which teachers possess after their academic formation,<br>the novices are obliged to learn at a very quick pace the functioning of the dynamic school. With so<br>much novelty, evaluation stands out in the broad sense and also as the receiver of all information. In<br>this paper we examine the method of work by means of an example, in projects of statistical education<br>and their evaluation through a trainee portfolio analysing the information obtained and using it as a<br>source to regulate the inter-action in the classroom. This will help us to appreciate the grade of<br>knowledge acquired by the students in certain concepts of statistics proposed in the Spanish curriculum<br>for students from 15-16 years in obligatory secondary education.

We compare two methods of recording data and making graphic displays: a standard paper-and-pencil technique and a "data-cards" approach in which students record case information on individual cards which they then arrange to make displays. Students using the data cards produced displays that tended to be more complex and informative than displays made by those in the paper-and-pencil group. We explore plausible explanations for this difference by examining structural aspects of the two approaches, such as the saliency of the case and the use of space in organizing the information. Our results call into question the wisdom of the current practice of introducing young students to particular graph types and of the idea that they need to master handling of univariate data before they move on to multivariate data.

The aim of this paper is to attempt an answer to the questions posed in the title. Geographically or economically speaking, countries vary from developing to developed, from the North to the South, and from East to West. Within each geographical context, let alone amongst them, there is a wide range of jobs, occupations, positions, etc., each of which has its own data analysis requirements. These requirements vary to suit macro versus micro levels; high management and executive levels versus middle, low and other managerial levels; and research and policy making levels versus administrators and clerks. Consequently, given the complexity of situations in which data analysis will be used there cannot be unique approaches to teaching data analysis. Such is the situation in the world of work. However, the situation is not much different in the world of education. The variety of audiences who can, or wish to, be taught data analysis include parents, teachers and business people in different sectors, government employees who, in turn, are scattered among different ministries and departments which certainly are not unique. What are the implications of this diversity for teaching data analysis? The remainder of the paper is organized into five sections: (a) The teaching/learning load and the teacher's role; (b) School children and the future; (c) A framework for a course on data analysis for schools; (d) A course on data analysis for schools: and (e) Conclusion