Did these five H-H values correspond to student pairs whose test scores failed the response-independence hypothesis, as indexed by Wesolowsky’s SCheck program? No: using its default settings, SCheck suggested that only the two highest H-H values corresponded to student pairs whose hypothesis could be rejected.
Rejection of the null hypothesis is not a fail-proof process – there is always the possibility of a Type I error, always some chance that a statistically-significant test statistic will be a false positive. SCheck goes to great lengths to minimize false positives, as did Harpp and Hogan (1993) when they set their test z-score minimum at 5.0.
To check on the possibility of false positives, we can ask if the two student pairs sat the test at the same venue, and were seated next to each other. If they were not, if they were miles apart when sitting the test, then we’d rather reasonably assume they had no chance whatsoever to cheat, and we’d conclude that both the H-H index and the SCheck significance test had returned a false positive.