  To determine whether some often-used lexical association measures assign high
scores to n-grams that chance could have produced as frequently as observed, we
used an extension of Fisher's exact test to sequences longer than two words to
analyse a corpus of four million words. The results, based on the
precision-recall curve and a new index called chance-corrected average
precision, show that, as expected, simple-ll is extremely effective. They also
show, however, that MI3 is more efficient than the other hypothesis tests-based
measures and even reaches a performance level almost equal to simple-ll for
3-grams. It is additionally observed that some measures are more efficient for
3-grams than for 2-grams, while others stagnate.
