Conference Paper

  • The relationship between mathematics and statistical reasoning frequently receives comment (Vere-Jones 1995, Moore 1997); however most of the research into the area tends to focus on mathematics anxiety. Gnaldi (2003) showed that in a statistics course for psychologists, the statistical understanding of students at the end of the course depended on students' basic numeracy, rather than the number or level of previous mathematics courses the student had undertaken. As part of a study into the development of statistical thinking at the interface between secondary and tertiary education, students enrolled in an introductory data analysis subject were assessed regarding their statistical reasoning, basic numeracy skills, mathematics background and attitudes towards statistics. This work reports on some key relationships between these factors and in particular the importance of numeracy to statistical reasoning.

  • This paper is part of a research study, the objective of which is to investigate the meaning of confidence intervals for first year students in the Statistics course in the Universidad Nacional de Rosario. Within the framework of Godino's theory (1999), by means of students' dialogues in front of the computer, we try to surmise the presence of the diverse elements of meaning - extensive, ostensive, actuating, intensive and validating - which reveal the topic comprehension. Statistical inference is one of the largest branches of Statistics and a fundamental methodological tool in the empiric sciences, in particular. It allows us to quantify our confidence in conclusions drawn from random samples, and therefore, to verify our impressions by means of calculations (Batanero, 2001); hence, the importance of an updated teaching.

  • Instructors of statistics who teach non-statistics majors possess varied academic backgrounds, and hence it is reasonable to expect variability in their content knowledge, and pedagogical approach. The aim of this study was to determine the specific course(s) that contributed mostly to instructors' understanding of statistics. Courses reported were described as advanced or graduate level, and classified as application-based, math, multivariate, probability, and research. The majority, 9 (56%) attributed their understanding of statistics to either an application-based or research course, and of those, 7 (44%) reported negative feelings about their introductory courses. These findings underscore the importance of authentic activities, and constructivist pedagogy toward facilitating statistical literacy. Research is needed to determine the effect of instructors' academic preparation on their knowledge, attitudes, and practices.

  • In this age of information technology vast amounts of data are generated from many different processes which necessitate the practice of statistics in some form or other. Many third world students grapple with understanding the subject of Statistics and the success of teaching statistics depends on finding a satisfactory answer to many of the questions asked by the majority of students. This paper highlights the misconceptions that students have about statistics and shows that dispelling the myths and prejudices eases the teaching of the subject matter and the acceptance of statistics as a rewarding career.

  • Periodic regression is seldom included in syllabus of statistical courses. However, data following periodic or cyclic behavior are often encountered, especially in agriculture. Therefore, we think that this type of regression should be taught to students of agriculture, even in basic courses of statistics. In this paper we propose the way of teaching periodic regression through examples usually encountered in practice. The analysis of data will be based on the graphical interpretation, which would provide the visual display of the investigated problems as well.

  • Supervised classification or pattern recognition is a method to solve decision problems in Social Sciences. It is organized on the basis of specific sets of predictor variables and the existence of classes known a priori. Based on a training sample, its main objective is to construct a classification rule in order to predict the class to which a new object belongs. Nowadays, the availability and efficacy of powerful computers have made possible many advances in this field, both in Statistics and Computer Sciences. In this section, different methods will be discussed and illustrated with the results obtained in several applications. The following topics will be dealt with: Parametric Discriminant Analysis, Non-parametric Discriminant Analysis, Logistic Discriminant Analysis, Neuronal Networks, Recursive Partitioning and Estimation of Error Rates.

  • Ever since its founding, the Pedagogy Department at the Complutense University of Madrid has considered statistics to be fundamental instrument in the training of educational researchers. For this reason, the department has made every effort for the teaching of statistics to keep pace with the field itself. However, the results so far have been unsatisfactory. These negative results, combined with Pedagogy students' initial limited ability in statistical processing, point out the need for new techniques that can be used to teach research methods in education.

  • This paper is aimed at identifying the invariants employed by teachers to understand the variation concept. Ten Mathematics teachers were involved in this research, in a process of continuing formation lasting 54 hours. During the early discussions with these teachers it was possible to identify the absence of such concept among them. When working with quantitative data we realized the teachers knew the algorithm for the calculation of standard deviation, although they were not able to interpret the results they obtained. At the end of the process we used an exercise to diagnose possible changes in the conceptual field of variation. Only one lady teacher was able to clearly identify data variation and the mean variation. Although we worked with such a small groups of teachers, we could notice that data variation is an intuitive concept, which does not happen in terms of standard deviation, which is extremely hard to interpret.

  • The research discussed in the paper comes from a multifaceted program for the teaching and learning of early statistical reasoning in Cyprus. The overall aim of the program is to enhance the quality of statistics education offered in Cypriot elementary schools by facilitating professional development of teachers using exemplary technological and educational tools and resources. As part of the program, professional development seminars for the teaching of statistics with the use of Tinkerplots@ - a dynamic data-visualization package designed specifically for young learners - were designed and offered to elementary school teachers. The article discusses insights gained from the seminars regarding the ways in which computer visualization tools can enhance teachers' content and pedagogical knowledge of statistics.

  • In this report we present a proposal to work in the classroom starting from some theoretical and conceptual elements that might be used for teachers when facing the problem of teaching the main probability and statistics concepts in the Colombian context. We first reflect on the knowledge that is offered in the country and then outline a didactic work approach from exploratory data analysis.