Inferential Statistics: Understanding Expert Knowledge and its Implications for Statistics Education

Abstract

This study investigated the knowledge base necessary for choosing appropriate statistical techniques in applied research. In this study, we compared knowledge used by six experts and six novices in two types of statistical tasks. The tasks were: 1) comparing research scenarios from the perspective of choosing a statistical technique, and 2) direct comparison of statistical techniques. The framework was based on expert knowledge in inferential statistics using the repertory grid technique for data collection. A qualitative analysis of data showed that of the three types of expert knowledge, research design knowledge comprised the biggest portion, with theoretical and procedural knowledge comprising relatively smaller parts. Little difference was observed between experts and novices in extensiveness of knowledge use, although experts' knowledge use was found to be more integrated than novices'. Finally, two implications were drawn regarding how to better teach selection skills in statistics education: (1) statistical techniques should be taught in relation to relevant research designs, and (2) conceptual connections between statistical techniques should be explicitly taught.

• Knowledge structure
• Selection skills
• Statistical expertise
• Statistical literacy
• Statistical techniques

Acknowledgements

This research is based on a dissertation study (Alacaci 1998) by the author at the University of Pittsburgh, School of Education, under the guidance of Dr. Ellen Ansell. The author gratefully acknowledges her mentorship and support. The help of committee members Drs. Edward Silver, Martin Cohen and Louis Pingel is also appreciated. This research was supported by a grant from the Faculty and Student Research Award of the School of Education at the University of Pittsburgh. The author would also like to thank Francis Di Vesta, Tom Short and the two anonymous reviewers whose comments improved the quality of this paper significantly.