What are the limitations of statistical tests?

What are the limitations of statistical tests?

Statistical tests have several limitations, including assumptions about data distribution, sample size sensitivity, and potential for misinterpretation.

Can you explain the assumptions that these tests make?

Sure! Common assumptions include normality, independence of observations, and homogeneity of variance, which can affect the validity of results.

What happens if these assumptions are violated?

If assumptions are violated, the results may be unreliable, leading to incorrect conclusions. Alternative methods or transformations may be needed.

Are there any specific tests that are more robust to these limitations?

Yes, non-parametric tests like the Mann-Whitney U test or bootstrapping methods can be more robust when assumptions are not met.

How can I determine which statistical test to use?

Choosing a statistical test depends on your data type, distribution, and research question. It's important to understand your data first.