Table 9. Results of the Mann-Whitney U test and the t-test comparing boundary shift for the three forms of iterated algorithmic bias with class-dependent human action probability ratio 1:1 and 10:1.

The effect size is calculated as (Boundary|_{ratio = 1: 1} − Boundary|_{ratio = 10: 1})/standard.dev at time t = 200. Both Filter bias and active learning bias show no significant difference between the two ratios. On the other hand, random selection leads to more points predicted to be in class y = 1.

	Filter Bias	Active Learning	Random Selection
Mann-Whitney test p-value	0.038	0.30	7.8e- 9
t-test p-value	0.07	0.18	1.4e- 9
effect size	-0.4	0.04	-1.28