The Chi-Squared test reflects the probability that the distribution of an outcome
is random or likely influenced by some other factor, like bias. Chi-Squared can be
used to assess whether, for example, the distribution of loan approvals for one
group significantly different from the distribution for another group. A statistically
significant Chi-Squared result (p < 0.05) strongly suggests that an adverse outcome
for a protected group is unlikely to have occurred by chance, and may indicate
potential bias in the underwriting process. A Chi-Squared result (p < 0.01) provides
even stronger evidence that the adverse outcome has not occurred by chance.
Although there are no concrete fairness thresholds, regulators may find:
