Paper Reading #20

The aligned rank transform for nonparametric factorial analyses using only anova procedures

Authors:

Jacob O. Wobbrock - University of Washington, Seattle, Washington, USA

Leah Findlater - University of Washington, Seattle, Washington, USA

Darren Gergle - Northwestern University, Chicago, Illinois, USA

James J. Higgins - Kansas State University, Manhattan, Kansas, USA

Proceeding
CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems

Summary

ANOVA is short for ANalysis Of VAriance. Nonparametric data in experiments with multiple factors occur in the field of HCI. Analyzing interaction effects with this type of data is impossible with traditional analyses. The Aligned Rand Transform is able to analyze this type of data.

Hypothesis

The researchers propose an algorithm and tools for analyzing multi-factor non-parametric data.

Methods

ARTool and ARTweb are programs that utilize the ART algorithm. The algorithm starts by computing each cell's residual value. Next the estimated n-way effects are computed using alternating positive and negative summations. Then the residual is added to the estimated effects. Last the average ranks are assigned and a full factorial ANOVA is performed on the ranks.

Results

The ARTool was used to evaluate a satisfaction survey for how satisfied they were on a test interface. The data was analyzed with ANOVA and with ART. The ANOVA test did not show any interaction but the ART did. The researchers hypothesized the interaction would exist and the ARTool was able to prove it for them.

Conclusion

I have yet to take statistics, so much of this is quite confusing. I do know that determining correlations in data is important for finding unknown relations. The best example I know about this is the statistics Blogger and YouTube offer (both being from Google) for individual uploads. The paper notes that this algorithm is accessible to anyone "familiar with the F-test," which I am not. After skimming through what it is, it seems there is quite a bit of statistics I need to understand before fully understanding the ART algorithm.