The Mann-Whitney U test is most appropriately used to compare which type of data?

The Mann-Whitney U test is specifically designed for nonparametric data, making it suitable for situations where the assumptions of parametric tests (such as the t-test) cannot be met. Nonparametric tests do not rely on data being normally distributed and are ideal when dealing with ordinal data or continuous data that do not meet parametric criteria. The Mann-Whitney U test ranks the data from both groups being compared and evaluates whether the distributions of these groups differ significantly.

This characteristic allows it to be particularly useful in many clinical and research scenarios encountered in cardiology and other fields, where sample sizes may be small or data may be skewed. It is also robust against outliers, making it versatile in practice. Therefore, using the Mann-Whitney U test aligns perfectly with the properties of nonparametric data, validating the choice of that option for comparison.