This paper is from Session 3E: Learning to teach data-based statistics at school and tertiary level

which comes under Topic 3: Learning to teach statistics

Other papers under session 3E ... 3E1: Towards evaluation criteria for coherence of a data-based statistics... 3E3: Models of teacher preparation designed around the GAISE Framework

(Monday 12th, 11:00-12:30)

Some issues of data production in teaching statistics

Presenter

• Carl Lee (Central Michigan University, United States)

Abstract

Statistics educators, for a long time, have stressed the importance of using real data and focusing on variability of data in teaching statistics. Real data are messy. Due to the difficulty of creating a ‘real’ process of data production in a classroom setting, the issues of data production seem to be ignored in teaching statistics. Some of the issues may include (a) choice of measurement units, (b) robustness of measuring techniques, (c) the importance of operational definition, (d) subjective sampling vs. random sampling (e) observational vs. experimental studies (f) outliers Vs. errors, and (g) underlying target population. The use of real-time hands-on activities to teach students how to handle the issues of data production in a classroom setting is demonstrated.

Other papers under session 3E ... 3E1: Towards evaluation criteria for coherence of a data-based statistics... 3E3: Models of teacher preparation designed around the GAISE Framework