Literature Index

The business world offers many opportunities for statisticians, especially in advising decision-making processes. Elementary school age youngsters in their everyday lives also are confronted with decision situations, some with a business flavor, where a rudimentary understanding of statistics may prove useful. However, the pedagogical concerns of making the study of these situations accessible at an early age often prohibits consideration until the problems can be discussed on a high mathematical level. Consider, for example, the classic "Newsboy's Problem" concerning a newspaper seller attempting to maximize profit. Children can appreciate such a problem; indeed they may have paper routes or operate newspaper stands themselves. SHUNDA'S NEWSSTAND provides an excellent example of how an operations research problem involving statistics in a decision-making context can be presented at the elementary school level. A second example described involves Population Growth.

This study attempts to construct the profiles of two types of statistics learners: namely those<br>with a positive and a negative attitude towards statistics. The contribution of this work lies in<br>its attempt to characterize each profile of learner by relating to his/her perceived attitudes<br>toward statistics, types of learners, mode of study, program structure, age, gender and<br>learners' evaluation towards the statistics course. These variables are used as predictors that<br>discriminate learners with positive and negative attitudes toward statistics. The results<br>indicate that learners with positive attitudes can be reliably distinguished from learners with<br>negative attitudes toward statistics. This then can assist instructors to optimize the teaching<br>and learning of statistics in the classroom.

As part of a research project on students' understanding of variability in statistics, 272 students, (84 middle school and 188 secondary school, grades 6 - 12) were surveyed on a series of tasks involving repeated sampling. Students' reasoning on the tasks predominantly fell into three types: additive, proportional, or distributional, depending on whether their explanations were driven by frequencies, by relative frequencies, or by both expected proportions and spreads. A high percentage of students' predominant form of reasoning was additive on these tasks. When secondary students were presented with a second series of sampling tasks involving a larger mixture and a larger sample size, they were more likely to predict extreme values than for the smaller mixture and sample size. In order for students to develop their intuition for what to expect in dichotomous sampling experiments, teachers and curriculum developers need to draw explicit attention to the power of proportional reasoning in sampling tasks. Likewise, in order for students to develop their sense of expected variation in a sampling experiment, they need a lot of experience in predicting outcomes, and then comparing their predictions to actual data.

Nowadays, the importance of affectivity in statistics education is widely acknowledged. In the past two decades a large number of instruments to measure attitudes and anxiety toward statistics have been developed in order to assess the influence of emotional factor on students' training. However, many of these instruments have not been analysed in depth and their psychometric properties have not properly been assessed. The aim of this paper is revising the research works that have contributed empirical evidence for the reliability and validity of these instruments. Our results suggest the need for more research about instruments to measure attitudes and anxiety about statistics. We conclude by suggesting some priority research areas that might be relevant in future studies on this topic.