Discriminating "Signal" and "Noise" in Computer-Generated Data

Author(s)
Prodromou, Theodosia
Pratt, David
Publication Date
2010
Abstract
This paper presents a case study of a group of students (age 14-15) as they use a computer-based domain of stochastic abstraction to begin to view spread or noise as dispersion from the signal. The results show that carefully designed computer tools, in which probability distribution is used as a generator of data, can facilitate the discrimination of signal and noise. This computational affordance of distribution is seen as related to classical statistical methods that aim to separate main effect from random error. In this study, we have seen how signal and noise can be recognised by students as an aspect of distribution. Students' discussion of computer-generated data and their sketches of the distribution express the idea that more variation is centred close to the signal, and less variation is located further away from it.
Citation
Proceedings of the Thirty Fourth International Conference for the Psychology of Mathematics Education, v.4, p. 57-64
Link
Publisher
International Group for the Psychology of Mathematics Education (IGPME)
Series
PME Conference Proceedings
Title
Discriminating "Signal" and "Noise" in Computer-Generated Data
Type of document
Conference Publication
Entity Type
Publication

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