The Chi-Squared test is a statistical method used to determine if there is a significant association between categorical variables. It is commonly applied in hypothesis testing to assess how well observed data fit with expected data under a specific hypothesis.

There are two main types of Chi-Squared tests: the Chi-Squared Goodness of Fit Test and the Chi-Squared Test of Independence. The Goodness of Fit Test evaluates whether a sample distribution matches an expected distribution, while the Test of Independence assesses whether two categorical variables are independent of each other in a contingency table format.

To perform a Chi-Squared test, you calculate the Chi-Squared statistic using the formula: χ² = Σ((O - E)² / E), where O represents the observed frequencies and E represents the expected frequencies. The resulting statistic is then compared to a critical value from the Chi-Squared distribution to determine significance ¹²³⁴⁵.

If you have more specific questions about the Chi-Squared test or its applications, feel free to ask!