I appreciate that you guys might not be statisticians, but if you're going to try and analyze data like this, you simply must address survival bias. As it stands, these data are meaningless unless you assume dropouts are completely unrelated to your screening.
You claim doing well on the Fizzbuzz wasn't correlated with interview performance, but you also said "We saw twice the drop off rate on the coding problems as we saw on the quiz."
An alternate explanation for your finding then is, more low-quality candidates drop out of the process when given FizzBuzz, leaving a relatively homogeneous pool of higher-quality candidates for the later interview. This effectively reduces the ratio of meaningful interindividual differences relative to noise, which will reduce the correlations.
In all likelihood, both of your correlations are low, but the idea that coding is less predictive than a quiz could be purely a statistical fluke due to survivor bias.
You claim doing well on the Fizzbuzz wasn't correlated with interview performance, but you also said "We saw twice the drop off rate on the coding problems as we saw on the quiz."
An alternate explanation for your finding then is, more low-quality candidates drop out of the process when given FizzBuzz, leaving a relatively homogeneous pool of higher-quality candidates for the later interview. This effectively reduces the ratio of meaningful interindividual differences relative to noise, which will reduce the correlations.
In all likelihood, both of your correlations are low, but the idea that coding is less predictive than a quiz could be purely a statistical fluke due to survivor bias.