The Chi-squared test is a statistical method used to determine if there is a significant association between categorical variables. It compares the observed frequencies of events in different categories to the frequencies expected under the assumption of no association. This helps researchers understand if the differences in data are due to chance or if they indicate a real relationship. There are two main types of Chi-squared tests: the test of independence, which assesses whether two categorical variables are related, and the goodness-of-fit test, which checks if a sample distribution matches a theoretical distribution. Both tests provide valuable insights in fields like social sciences and health research.