Visualization of Differences in Data Measuring Mathematical Skills
Source: University of Ostrava
Identification of significant differences in sets of data is a common task of data mining. This paper describes a novel visualization technique that allows the user to interactively explore and analyze differences in mean values of analyzed attributes. Statistical tests of hypotheses are used to identify the significant differences and the results are then presented using Hasse diagrams. The presented technique has been tested on real data coming from pedagogical tests focused on evaluation of mathematical skills of secondary school students in Czech Republic. The results show that the proposed tool provides comprehensible representation of the data.