Students’ interpretations of categorical data using dynamic graphical representations

<p>Statistical association is an important concept in statistics. An exploratory study examined how students reason about statistical association utilizing graphical representations constructed with CODAP, a dynamic statistical graphing software. Task-based interviews were conducted with three 6th grade students prior to formal instruction. Students’ conceptions of a statistical relationship, proportional reasoning skill level, ability to interpret bivariate categorical graphs (particularly segmented bar graphs and two-way binned plots), and ability to identify association of two categorical variables were all investigated through interview tasks and responses to inquiry. Students were found to have developing proportional reasoning skills and struggled to correctly define and identify association. These results were compared to a previous study which asked students to analyze pre-constructed graphs. Students were more successful interpreting graphs that they constructed than pre-constructed graphs. These results have curricular and future research implications.</p>

Name thesis:degree_name

Master of Arts (MA)

Level thesis:degree_level

Open Access Thesis

Discipline thesis:degree_discipline

Mathematics

Year dc:date.available

2018

Author dc:creator

• Eide, Adam

Contributors dc:contributor

• Stephanie Casey, Ph.D.
• Andrew Ross, Ph.D.
• Carla Tayeh, Ph.D.

• bivariate
• categorical
• data
• proportional
• software
• statistics
• Mathematics
• Science and Mathematics Education
• Statistics and Probability

Repository record dc:identifier

https://commons.emich.edu/theses/955

OAI identifier oai:identifier

oai:commons.emich.edu:theses-2324