American Board of Surgery Qualifying Exam (ABS QE) 2025 – 400 Free Practice Questions to Pass the Exam

The Wilcoxon rank-sum test is particularly suitable for skewed or ordinal data because it is a non-parametric statistical test. This means it does not assume that the data follows a normal distribution, which is a requirement for parametric tests like the t-test that compare means of continuous data.

When dealing with ordinal data, the values represent a rank order; however, the actual distances between the ranks may not be known or may not be equal. The Wilcoxon rank-sum test assesses whether there is a significant difference between the distributions of two independent groups by ranking all the data and comparing the sum of ranks between the groups. This approach effectively handles the situations where data may be skewed or when the scale of measurement is ordinal.

The context behind the other options clarifies why they are less suitable. Nominal data consists of categories without any inherent order, making it inappropriate for a rank-based test. Normal continuous data suggests the assumption of normality, which fits better with parametric tests rather than the non-parametric Wilcoxon test. Lastly, the Wilcoxon rank-sum test is designed for comparing two groups specifically, not for data with more than two groups, which would require different statistical techniques such as the Kruskal