Despite their advantages, there are some limitations to consider:
Power: Non-parametric tests generally have less statistical power than parametric tests, meaning there is a higher chance of Type II error. Information Loss: These tests do not use the actual data values but rather their ranks, which may lead to the loss of information. Complex Interpretation: Results can sometimes be more difficult to interpret, especially when dealing with large datasets.
