I am doing an analysis on a “a priori segmentation”. In order to examine significant differences between the two segments crosstabs and the chi-square test were used.
Type of variables: categorical
Sample size: 253
Program used: SPSS version 21.
Problem: in several ways the assumption for a chi-square test is not met. Under some tables it is written (e.g.): 4 cells (22.2%) have expected count less than 5. The minimum expected count is 1.85 or 7 cells (50.0%) have expected count less than 5. The minimum expected count is .26. or 10 cells (62.5%) have expected count less than 5. The minimum expected count is .26.
What should be done in this case? Should the chi-square test be avoided? Which test could be used instead? The literature says that for 2x2 contingency tables a Fisher’s exact test can be used. What should be done with bigger contingency tables (variables that entail several categories)?