Tip: To gather records for later use, such as citation listing, click an item's Add to My Collection + icon. Click My Collection at any time to see your accumulated records. My Collection lasts for the duration of your browser session.
Prodromou T, Pratt D. Discriminating "Signal" and "Noise" in Computer-Generated Data. 2010.
Please use this identifier to cite or link to this item: http://e-publications.une.edu.au/1959.11/8374
Discriminating "Signal" and "Noise" in Computer-Generated Data
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.