Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/8374
Title: Discriminating "Signal" and "Noise" in Computer-Generated Data
Contributor(s): Prodromou, Theodosia  (author)orcid ; Pratt, David (author)
Publication Date: 2010
Handle Link: https://hdl.handle.net/1959.11/8374
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.
Publication Type: Conference Publication
Conference Name: PME 34: 34th Conference of the International Group for the Psychology of Mathematics Education - "Mathematics in Different Settings", Belo Horizonte, Brazil, 18th - 23rd July, 2010
Conference Details: PME 34: 34th Conference of the International Group for the Psychology of Mathematics Education - "Mathematics in Different Settings", Belo Horizonte, Brazil, 18th - 23rd July, 2010
Source of Publication: Proceedings of the Thirty Fourth International Conference for the Psychology of Mathematics Education, v.4, p. 57-64
Publisher: International Group for the Psychology of Mathematics Education
Place of Publication: Belo Horizonte, Brazil
Field of Research (FOR): 010406 Stochastic Analysis and Modelling
010404 Probability Theory
010405 Statistical Theory
Socio-Economic Outcome Codes: 930203 Teaching and Instruction Technologies
930102 Learner and Learning Processes
930199 Learner and Learning not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Other Links: http://pme34.lcc.ufmg.br
http://trove.nla.gov.au/work/38986776
Series Name: PME Conference Proceedings
Series Number : 34
Statistics to Oct 2018: Visitors: 615
Views: 643
Downloads: 0
Appears in Collections:Conference Publication
School of Education

Files in This Item:
4 files
File Description SizeFormat 
Show full item record

Page view(s)

116
checked on Mar 4, 2019
Google Media

Google ScholarTM

Check


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.