Document Type
Conference Paper
Publication Date
Summer 7-28-2015
Abstract
A first lab experiment clearly illustrates that a glucose meter is actually an excellent source of both random and systematic error, much to the surprise to students and physicians alike. A histogram is constructed and the utility of the standard deviation and standard error to quantify the uncertainty in each measurement and in the mean value, respectively, is demonstrated. From the first lab on, students are challenged to express and interpret confidence intervals in order to form quantitative conclusions. Assessments reveal that many students find this to be surprisingly challenging.
Recommended Citation
Laing, William B. III and Bryant, Sean, "Quantifying Measurement Error in Digital Instruments" (2015). Faculty Works. 18.
https://knowledge.e.southern.edu/facworks_physics/18
Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Physics Commons, Statistics and Probability Commons