On understanding variability in data: a study of graph interpretation in an advanced experimental biology laboratory

Wolff-Michael Roth*, Shelby Temple

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)


Data analysis is constitutive of the discovery sciences. Few studies in mathematics education, however, investigate how people deal with (statistical) variability and statistical variance in the data to be interpreted. And even fewer, if any, focus on the uncertainties with which scientists wrestle before they are confident in the data they produce. The purpose of this study is to exhibit the work of coping with variability in one advanced research laboratory, as exemplified in a typical data analysis session. The study shows that when the scientists are confronted with novel data, their understanding of the variability does not arise in straightforward fashion, and a lot of normally invisible (interactional) work is required to constitute understanding. Tentative conclusions are provided for the implication to mathematics education.

Original languageEnglish
Pages (from-to)359-376
Number of pages18
JournalEducational Studies in Mathematics
Issue number3
Publication statusPublished - Jul 2014


  • Variability
  • Data interpretation
  • Discovery sciences
  • Data analysis
  • Mathematical practices

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