Section 023 · Chapter 4, Statistical Tests for AI Quality
P-Values: Evidence, Not Permission
P-values can support a comparison, but they do not decide whether a product is safe, useful, or worth shipping.
p-valuep values evidence permission
What to do
- Version B reduced automatic refunds from 18% of conversations to 14%, and the p-value is 0.003.
- Define runnable checks that exercise p-value and p values evidence permission.
- Set acceptable outcomes and blocker failures for p-value and p values evidence permission before running the evaluation.
Evidence to preserve
- Preserve the inputs, versions, configurations, raw outcomes, and results for p-value, p values evidence permission needed to reproduce work on P-Values: Evidence, Not Permission.
- Report results for p-value, p values evidence permission by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.
Expert note
Expert reports treat p-values as continuous evidence, not as a yes/no permission slip. A useful report pairs the p-value with the other facts needed to make a responsible decision:
Continue the conversation
Apply this to your context.
Save your product context once, then open a focused conversation that combines it with this concept.
Cite this page
Jason Arbon. "P-Values: Evidence, Not Permission." Testing AI Knowledge Edition, section 23.
https://jarbon.ai/testing-ai/knowledge/ch023-p-values-evidence-permission.html