Parallel discussion of classical and Bayesian ways as an introduction to statistical inference

Abstract

The purpose of this paper is to report on the conception and some results of a long-term university research project in Budapest. The study is based on an innovative idea of teaching the basic notions of classical and Bayesian inferential statistics parallel to each other to teacher students. Our research is driven by questions like: Do students understand probability and statistical methods better by focussing on subjective and objective interpretations of probability throughout the course? Do they understand classical inferential statistics better if they study Bayesian ways, too? While the course on probability and statistics has been avoided for years, the students are starting to accept the "parallel" design. There is evidence that they understand the concepts better in this way. The results also support the thesis that students' views and beliefs on mathematics decisively influence work in their later profession. Finally, the design of the course integrates reflections on philosophical problems as well, which enhances a wider picture about modern mathematics and its applications. © 2009 by GOKKUSAGI.