The Chi-Squared distribution, denoted as χ², is a continuous probability distribution widely used in statistical hypothesis testing. It arises when summing the squares of independent standard normal random variables, making it essential for various statistical analyses. This distribution is particularly significant in goodness-of-fit tests and tests for independence in contingency tables. As the sample size increases, the Chi-Squared distribution approaches a normal distribution due to the central limit theorem. Its properties and applications make it a fundamental tool in statistics, especially in fields like data science and machine learning, where understanding relationships between categorical variables is crucial.