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Interpreting experimental data in high school experiments can be a difficulttask for students, especially when there is large variation in the data. At thesame time, calculating the standard deviation poses a challenge for students.In this article, we look at alternative uncertainty measures to describe thevariation in data sets. A comparison is done in terms of mathematicalcomplexity and statistical quality. The determination of mathematicalcomplexity is based on different mathematics curricula. The statistical qualityis determined using a Monte Carlo simulation in which these uncertaintymeasures are compared to the standard deviation. Results indicate that anincrease in complexity goes hand in hand with quality. Additionally, we proposea sequence of these uncertainty measures with increasing mathematicalcomplexity and increasing quality. As such, this work provides a theoreticalbackground to implement uncertainty measures suitable for different educationallevels.

Comparing Different Uncertainty Measures to Quantify Measurement Uncertainties in High School Science Experiments