A Pilot Study Teaching Metrology in an Introductory Statistics Course


Authors: 
Emily Casleton, Amy Beyler, Ulrike Genschel, and Alyson Wilson
Year: 
2014
URL: 
http://ww2.amstat.org/publications/jse/v22n3/casleton.pdf
Abstract: 

Undergraduate students who have just completed an introductory statistics course often lack deep
understanding of variability and enthusiasm for the field of statistics. This paper argues that by
introducing the commonly underemphasized concept of measurement error, students will have a
better chance of attaining both. We further present lecture materials and activities that introduce
metrology, the science of measurement, which were developed and tested in a pilot study at Iowa
State University. These materials explain how to characterize sources of variability in a dataset,
in a way that is natural and accessible because the sources of variability are observable.
Everyday examples of measurements, such as the amount of gasoline pumped into a car, are
presented, and the consequences of variability within those measurements are discussed. To
gauge the success of the material, students’ initial and subsequent understanding of variability
and their attitude toward the usefulness of statistics were analyzed in a comparative study.
Questions from the CAOS and ARTIST assessments that pertain to using variability to make comparisons, understanding the standard deviation, and using graphical representations of
variability were included in the assessment. The results of the comparative study indicate that
most students who were exposed to the material improved their understanding of variability and
had a greater appreciation of the value of statistics.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education