The Friedman Test is a non-parametric statistical test used to detect differences in treatments across multiple test attempts. It is particularly useful when the same subjects are tested under different conditions, making it a repeated measures analysis. This test ranks the data for each subject and then analyzes the ranks to determine if there are significant differences among the treatments. This test is often applied in fields like psychology, medicine, and agriculture where researchers want to compare the effects of different interventions or conditions on the same group of subjects. It serves as an alternative to the ANOVA test when the assumptions of normality are not met.