The Chi-squared test is a statistical method used to determine if there is a significant association between categorical variables. It assesses how well observed data fit with expected data under a specific hypothesis. The test is particularly useful in various fields, including social sciences, biology, and machine learning, to evaluate the independence of variables or the goodness of fit of a model. By comparing the observed frequencies in each category to the expected frequencies, researchers can infer whether any deviations are due to chance or indicate a meaningful relationship. This makes the Chi-squared test a valuable tool for hypothesis testing.