A chisquare test is a hypothesis test that compares the observed distribution of your data to an expected distribution of data.
There are several types of chisquare tests:
 Chisquare goodnessoffit test
 Use this analysis to test how well a sample of categorical data fits a theoretical distribution.
 For example, you can test whether a die is fair by rolling the die many times and using a chisquare goodnessoffit test to determine whether the results follow a uniform distribution. In this case, the chisquare statistic quantifies how much the observed distribution of counts varies from the hypothesized distribution.
 Chisquare tests of association and independence
 The calculations for these tests are the same, but the question you're trying to answer may be different.

 Test of association: Use a test of association to determine whether one variable is associated with a different variable. For example, determine whether the sales for different colors of cars depends on the city where they are sold.
 Test of independence: Use a test of independence to determine whether the observed value of one variable depends on the observed value of a different variable. For example, determine whether the candidate that a person votes for is independent of the voter's gender.
Note
Minitab does not use Yates' correction factor when it performs a chisquare test.