The Mann-Whitney U-test is classified as:

The Mann-Whitney U-test is classified as a non-parametric test for two groups because it does not assume a normal distribution of the data, making it suitable for analyzing ordinal data or continuous data that do not meet the assumptions required for parametric tests.

This test is particularly useful when comparing two independent groups to determine whether one group tends to have larger values than the other. By ranking all the values from both groups together and then comparing the ranks, the Mann-Whitney U-test assesses the differences in distributions between the two groups without necessitating the assumptions that come with parametric tests, such as equal variances or normality.

In contrast, parametric tests rely on specific distributional assumptions, which is why the Mann-Whitney U-test is preferred in scenarios where those assumptions cannot be satisfied. Other options mentioned, such as ANOVA, apply to multiple group comparisons or involve different data types, further differentiating the Mann-Whitney from those procedures. Therefore, the classification of the Mann-Whitney U-test as a non-parametric test for two groups is accurate and reflects its appropriate application in statistical analysis.