Chi-Square+Test

When should a Chi-Square test be used?

Use the chi (pronounced KY as in sky) square test to look at whether actual data differ from a random distribution. For example, say you want to find out whether students prefer particular T-shirt colors. Assume there are five different colors and each student could get one free at registration (there are enough so that everyone could choose the same color). If people chose at random, the proportion of each color chosen would be equal (about 20% of the total shirts chosen would be in each category). You might not be surprised to find 19% of the shirts chosen were red and 21% were black, but when do you have enough evidence to say people are choosing them non-randomly? This test will tell you. http://depts.alverno.edu/nsmt/stats.htm

Chi square tests can only be used on actual numbers and not on percentages, proportions, means, etc. http://math.hws.edu/javamath/ryan/ChiSquare.html

A non-parametric test, like chi square, is a rough estimate of confidence; it accepts weaker, less accurate data as input than parametric tests (like t-tests and analysis of variance, for example) and therefore has less status in the pantheon of statistical tests. Nonetheless, its limitations are also its strengths; because chi square is more 'forgiving' in the data it will accept, it can be used in a wide variety of research contexts. http://uk.answers.yahoo.com/question/index?qid=1006032701456