The Chi-Squared Distribution is a fundamental concept in statistics, particularly in hypothesis testing and confidence interval estimation. It arises from the sum of the squares of independent standard normal random variables, making it a special case of the Gamma Distribution. This distribution is widely used to assess how well observed data fit expected data, particularly in tests like the Chi-Squared test for independence and goodness of fit. The Chi-Squared Distribution is characterized by its degrees of freedom, which influence its shape and critical values, allowing statisticians to determine the significance of their results in various applications.