Chi-square test, usually written as χ2 test, is a statistical hypothesis test, which is used to analyze classified variables to determine whether the observed data is different from expectations. Chi-square test is a commonly used nonparametric test, which means that they do not assume the distribution of the data involved (for example, normal distribution). On the contrary, the test relies on parity distribution, which is a distribution of overall theoretical values.

Chi-square test has two main types:

1. Fitting chi-square test, which is used to test whether the observation frequency of a variable (the number of observations in each category) is different from the expected one. In other words, the test determines whether the sample distribution matches the population distribution.

Second, independent chi-square test, also known as joint chi-square test, compares two variables to see if they are different from each other.