Oct. 6, 2026

Here’s an idea: If you’re skeptical about the importance of checking statistical assumptions, then try running some sensitivity tests.

Run your analyses with and without assumption checks..

1. First, run the analysis using whatever heuristic you normally use.
2. Then fit a model rigorously, ensuring that its assumptions hold.
3. Compare the results.

Do this many times.

Is there a meaningful difference in the utility for your business situation?

• Do you invariably come to the same conclusions either way?
• Do you always calculate nearly identical predictions either way?
• Do you find the same levels of precision either way?

If your conclusions flip, predictions diverge substantially, and/or precision fluctuates, then you have empirically demonstrated why we bother with checking assumptions.