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Calcolatore Significatività Test A/B — Strumento online gratis

Il tuo test A/B è statisticamente significativo?

Calcola la significatività statistica dei test A/B. P-value, intervalli di confidenza, dimensione campione richiesta. Per marketer e product team.

🅰️ Control (A)

🅱️ Variant (B)

A conversion rate
0.00%
B conversion rate
0.00%
Uplift (relative)
0%
P-value
—
Enter numbers to see verdict
📚
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Free A/B test significance calculator — z-test for conversions

Calculate if your A/B test result is statistically significant. Two-proportion z-test with pooled variance. See p-value, confidence intervals, and clear verdict.

How to use this tool

  1. 1

    Enter visitors + conversions

    For both control (A) and variant (B): how many visitors and how many converted.

  2. 2

    Check significance

    See conversion rates, uplift %, p-value, confidence interval, statistical significance.

  3. 3

    Interpret result

    p < 0.05 = statistically significant. 95%+ confidence means the result isn't random noise.

Interpretation guide

  • p < 0.01: very strong evidence against null (99%+ confidence)
  • p < 0.05: standard "significant" threshold (95% confidence)
  • p < 0.10: weak evidence — don\'t call it significant
  • p ≥ 0.10: no significant difference detected

Frequently Asked Questions

What is statistical significance?
The probability that your observed difference is NOT random chance. p < 0.05 = less than 5% chance the difference is random — typically the threshold to consider a test "significant".
What sample size do I need?
Depends on your baseline conversion rate + minimum detectable effect. Rough rule: 1,000-10,000 per variant for typical web A/B tests. Low conversion rates (1%) need more samples; high rates (20%) need fewer.
What if my test is "not significant"?
Three options: (1) Run longer until sample size is adequate — but don't peek and stop early. (2) Accept the null hypothesis — the variants perform equally. (3) Bigger change next time — tiny differences need enormous samples to detect.
Z-test vs t-test vs chi-square?
For proportions (conversion rates), z-test with pooled variance is standard and what we use. For continuous metrics (revenue per visitor), t-test is more appropriate. This tool focuses on conversion-rate tests.
What's confidence interval?
The range where the true difference likely falls. "B is 15% better (CI: 8% to 22%)" means the real uplift is probably between 8-22% — we just don't know exactly where.

Punti chiave

  • A/B Test Significance Calcolatore is a free, browser-based calculator tool — is your a/b test result statistically significant?.
  • No signup, no downloads, no file uploads. Strumentos run in your browser; the few that need an outside service say so on the page.
  • Works on desktop, tablet, and mobile. Install as a PWA for offline access.

How to Use A/B Test Significance Calcolatore

  1. Open the tool: Launch A/B Test Significance Calcolatore on Strumentoolis — no account or download needed.
  2. Enter your data: Paste text, enter values, or select a file directly in your browser.
  3. Get instant results: Everything is processed locally — results appear immediately.
  4. Copy or download: Save your output or share it. Bookmark for quick access next time.

A/B Test Significance Calcolatore — Quick Facts

Prezzo
Gratis — senza limiti, senza filigrana, senza paywall
Privacy
Elaborato nel tuo browser. Gli strumenti che richiedono un servizio esterno lo indicano nella pagina. Le visite vengono conteggiate (Google Analytics).
Piattaforma
Qualsiasi browser moderno — desktop, tablet o mobile
Categoria
Calcolatore Strumentos on Strumentoolis
Offline
Works offline after first visit (Progressive Web App)
CaratteristicaDettagli
StrumentoA/B Test Significance Calcolatore
CategoriaCalcolatore
Registrazione richiestaNo
Caricamento fileNessuno — elaborato nel browser
Supporto mobileCompletamente adattivo
CostoGratis per sempre

Why Use A/B Test Significance Calcolatore?

You should try A/B Test Significance Calcolatore for a quick, private way to is your a/b test result statistically significant?. Processing happens in your browser and files are never uploaded; the few tools that need an outside service say so on the page.

On the other hand, dedicated APIs or desktop tools suit batch processing better. They also handle server-side automation. For everyday tasks, browser tools offer the best speed, privacy, and convenience.

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