To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.
In statistics, random samples are used to make generalizations, or inferences, about a population. If your data are not collected randomly, your results may not be valid.
Independence of the observations is a critical assumption for the chi-square test of association.
The chi-square test of association cannot be performed when categories of the variables overlap. Thus, each observation must be categorized into one and only one category.
Each sample should be large enough so that there is a reasonable chance of observing outcomes in every category. If the expected counts are too low, the p-value for the test may not be accurate. Minitab indicates, in your results, whether the expected counts are too low.