The standard confidence tests -- t-tests, G-tests, chi-squared tests, etc. -- based on distributions of independent, identically distributed (iid) data.
I'd have to think about it more, but I believe that btilly's examples are also the most intuitive reasons why independence matters. If your data is time-dependent, then assigning users to cohorts based on past performance lets the time dependency dominate. There may be other good examples.