p-Value
Definition
A p-value assesses the extremity of a result under the null hypothesis.
The probability of obtaining a result at least as extreme as the observed one under a specified null hypothesis.
Simply explained
It describes how likely data at least as extreme would be if the specified baseline assumption holds.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
An experiment reports p-value, effect size, and confidence interval together.
Limits and pitfalls
- Interpret as the probability of the null hypothesis, evidential strength, or practical relevance.
Origin & history
The p-value originated from early statistical significance tests and is now used with clear interpretational boundaries.
Use in mid-sized companies
- Possible application: An experiment reports p-value, effect size, and confidence interval together.
Frequently asked questions
What does p-value mean?
The probability of obtaining a result at least as extreme as the observed one under a specified null hypothesis. What errors should be avoided? Interpret as the probability of the null hypothesis, evidential strength, or practical relevance.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: