ABSTRACT
Chi-square is a simple statistical test that is used in a variety of ways. The very variety may lead to some confusion over what the test is good for, but the basic idea behind the test is that you calculate the difference between the scores you observed and the scores you would expect in that situation and then see whether the magnitude of the difference is large or small on the chi-square distribution. Chi-square is a non-parametric test, which means there are fewer assumptions for its use than there are for parametric tests. However, as we will see in this chapter, and as noted in Saito (1999) and Hatch and Lazaraton (1991), chi-square is a much-abused test in second language research studies, and often one of its assumptions (that of independence of data) is violated as a matter of course.
