A Randomization Test is a statistical method used to determine if the observed differences between groups are significant. It involves randomly rearranging the data to create a distribution of possible outcomes under the null hypothesis, which states that there is no effect or difference. By comparing the actual test statistic to this distribution, researchers can assess the likelihood of observing such a difference by chance. This test is particularly useful in situations where traditional parametric tests may not be appropriate, such as when data do not meet normality assumptions. It is commonly applied in fields like psychology, medicine, and social sciences to validate experimental results and ensure robust conclusions.