This document summarizes issues related to data-dependent selections and hypothesis testing. It discusses how preliminary inspection of data can influence test statistics and null hypotheses, potentially altering a test's ability to reliably detect discrepancies from the null. Two examples are provided: 1) "Hunting" through multiple independent tests and only reporting the most statistically significant result can incorrectly estimate the actual error rate as being much higher than the nominal rate of 5%. 2) Searching a DNA database and declaring a match with the first individual is different, as each non-match strengthens evidence for the inferred match. Adjusting is not needed as in the statistical "hunting" case. Selection of cut-offs or model