← DictionaryStatistical Significance
Whether a measured difference is unlikely to be the result of chance.
Whether the result is real or just noise.
What It Is
Statistical Significance sits on the Measurement side of the work, in the Testing area. The canonical meaning is whether a measured difference is unlikely to be the result of chance.
It is an idea you reason with rather than a deliverable you hand over, so two teams can both hold it correctly and still apply it differently. That is the version worth keeping, because it survives contact with a real project.
How It's Used
Statistical Significance earns its keep in reporting, analytics reviews and the arguments about what the numbers mean. It is usually discussed together with A/B Test, Conversion Rate and Report. The practical test is whether a decision changes because of it.
Why It Matters
The cost of being vague about Statistical Significance shows up later, not today. When it is unclear, reporting becomes a matter of opinion. It is worth pinning down before anyone builds on top of it.
It is a way of thinking, not a thing you can hold. Whether the result is real or just noise.
Termshift™
How the meaning shifts depending on who is using it, and where.
Practitioners use Statistical Significance as shorthand and expect no explanation — whether a measured difference is unlikely to be the result of chance.
Outside the industry, most people would just say: whether the result is real or just noise.
The Bottom Line
Treat Statistical Significance as a decision, not a description. Whether the result is real or just noise.