I worked with a Greek statistician who would always try to correct my pronunciation of the Greek letter chi. I would say “kai” and he would say something similar to “he”. It was like he and key combined. I can’t do it justice so I continued to say kai.
Regardless of how you pronounce it, the chi square test can be very useful. In fact, one of my business school classes was spent discussing the uses and assumptions of the chi square test. I won’t try to summarize a semester’s worth of material into a blog post. Rather, I wanted to point out that chi square tests are used for categorical data and the only “gotcha” is that you have to use the actual counts (rather than percentages). It is sensitive to cell counts and requires that there be at least 5 observations per cell.
The chi square test is a powerful statistical tool as it can tell you if there are significant differences between categories and it is the foundation for CHAID. CHAID is an abbreviation for CHi-square Automated Interaction Detector. It is one of the many segmentation techniques used in marketing and, if you plot out the tree that results from CHAID, it is a wonderfully visual way to see differences within your customers and/or prospects. For CHAID you will need to define a dependent variable and undergo EDA (exploratory data analysis) similar to a modeling project.