What Is Statistical Significance? Meaning, Formula and Examples
Statistical Significance explained in plain English: what it means, why it matters, how to calculate or apply it, a worked example and common mistakes.
Statistical Significance: Confidence that test differences are not due to chance. It prevents false conclusions.
What Statistical Significance means
Confidence that test differences are not due to chance.
Why it matters
It prevents false conclusions. Used alongside other metrics, it helps teams make better budget and strategy decisions.
How to calculate or apply it
Commonly evaluated at 95% confidence
Worked example
A test with enough conversions per variant.
Common mistake to avoid
Declaring winners prematurely.
Related terms
Conversion Rate
The percentage of visitors who complete a desired action.
Core Web Vitals
Google's metrics for loading (LCP), interactivity (INP) and visual stability (CLS).
A/B Testing
Comparing two versions to see which performs better.
Need help putting this into practice? Gravmo offers conversion rate optimisation. Get a proposal or message us on WhatsApp.
Frequently asked questions
Is Statistical Significance the same for every business?
No. Good values depend on your industry, margins, goals and data quality. Compare against your own history first.
Where can I see Statistical Significance?
Most values come from analytics, ad platforms, marketplace dashboards or your own sales records, depending on the metric.
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