The study compared different test statistics to see which ones are best at detecting patterns in data that follow a 'zig-zag' shape. The Discrete Kolmogorov-Smirnov test is good at finding decreasing trends, while the Pearson Chi-Square test is better at spotting increasing or bimodal patterns. The researchers found that the test statistics are more sensitive to certain patterns under the 'zig-zag' shape compared to a uniform distribution.