What type of data is the Wilcoxon signed-rank test intended for?

The Wilcoxon signed-rank test is designed specifically for analyzing paired or dependent measures, particularly when those measurements do not meet the assumption of normality often required for parametric tests. It is a non-parametric statistical test that evaluates whether the median of the differences between paired observations is significantly different from zero.

This makes it particularly useful in scenarios where you have two related samples, such as pre-test and post-test scores or measurements taken from the same subjects under two different conditions. The Wilcoxon signed-rank test assesses the ranks of the differences between paired observations, allowing it to effectively handle data that may be skewed or not normally distributed.

In contrast, the other options describe situations not suited for the Wilcoxon signed-rank test. Independent groups and large sample sizes are better suited for tests like the t-test, while multiple independent groups would typically require an ANOVA. Options that imply normally distributed data, like standard samples, also do not align with the intention of the Wilcoxon signed-rank test, which is more concerned with median differences in non-normal data contexts.