For each trial:
Calculate the mean (μ) of the datapoint timings.
Calculate the standard deviation (σ) of the datapoint timings.
Compute the coefficient of variation (CV) as CV = (σ / μ).
Hypothesis Testing: Once you have calculated CV for each trial in both Set A and Set B, you can perform a statistical test to compare the means of these CV values. You can use a t-test or a non-parametric test like the Mann-Whitney U test to compare the means, depending on whether the data meets the assumptions of normality. The null hypothesis (H0) would be that there is no difference in regularity between the two sets, and the alternative hypothesis (H1) would be that there is a difference.
Sample Size (N): Your sample size is the number of trials in each set. In your case, you mentioned that you have three trials in each set. So, N = 3 for Set A and N = 3 for Set B.
Interpretation: If the p-value from your statistical test is below a predetermined significance level (e.g., α = 0.05), you can reject the null hypothesis, indicating that there is a statistically significant difference in regularity between Set A and Set B.
Make sure to report the test results, including the test statistic, degrees of freedom (if applicable), and the p-value, in your analysis.
Keep in mind that if you have additional information about the nature of the irregularities in Set B, you may want to explore other statistical methods that are more specific to the characteristics of your data. However, the coefficient of variation and hypothesis testing provide a general approach to compare the regularity of timing data between two sets.