Which statement about Friedman's test is true?

Friedman's test is a non-parametric statistical test used to detect differences in treatments across multiple test attempts (related groups). The correct statement regarding Friedman's test is that it indicates overall differences among ranks. This means that it assesses whether there are statistically significant differences in the ranks of the related groups being compared.

In practical applications, researchers often use Friedman's test when they have repeated measures on the same subjects or when the design features matched samples, enabling the examination of differences in ratings or scores across those conditions. The test does not demonstrate where those differences lie, rather it signals that at least one condition is different from the others based on the ranking of the data.

The other options do not accurately describe the nature of Friedman's test. It is not specifically a post hoc test meant for independent groups; instead, it is used for related samples. Additionally, it isn’t focused on assessing the homogeneity of variances, which is more suitably evaluated by tests like Levene's test. Overall, the function of Friedman's test is primarily about comparing the rankings across different related conditions to ascertain if a significant difference exists among them.