This paper is from Session 3G: Developing understanding of statistical concepts: From undergraduate students to pre-service mathematics teachers
which comes under Topic 3: Statistics education at the post-secondary level
Paper 3G2 (Thursday 12th, 16:00-17:30)
Students’ preferences when choosing data Sets with different characteristics
Presenter
- Johannes Schulz (Humboldt University Berlin, Germany)
Co-authors
- Amy Masnick (Hofstra University, Hempstead, NY, United States)
- Burkhard Priemer (Humboldt University Berlin, Germany)
Abstract
We report a study on how 57 undergraduate students identify and evaluate characteristics of data sets like variance, sample size, number of decimal places of the values and repeated values. The findings suggest that the participants who are not experts in physics or statistics are able to notice obvious physical differences in data sets and find criteria to judge these datasets. They also have an intuition for the (mathematical) variance of the numbers, whether through spread or through the repetition of individual values. This means that students hold correct prior beliefs on what is important to look at when confronted with two different data sets which is a promising condition for developing future instructional curricula and exercises to improve understanding of data.