Source
Statistical method & guardrails — found from sitemap — Unbounce
Checked for Unbounce on 13 Oct 2026
- Page
- https://unbounce.com/landing-pages/statistical-significance/
- Checked
- 13 Oct 2026, 09:53 UTC
- How we may use it
- Public page, crawling permitted
Technical details
- type
- page
- http status
- 200
- content hash
- sha256:3cb0bcbe245130c119cdbe4060276ab66f02fed4ce4dca4608a15dbcb1e72f73
- permission
- robots_ok
- screenshot
- Screenshot on file (internal exhibit, not published)
Cited by
Facts read from this source
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Ab testing unlimited Report an error
“Unbounce lets you run unlimited A/B tests and calculates the statistical significance of each test for you so you can accurately conclude tests at the right time with confidence.”
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Free trial Report an error
“Get started with a 14-day free trial today.”
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Sample size calculator Report an error
“Your best bet for figuring out the ideal sample size for your test is using Unbounce’s A/B Test Duration and Sample Size calculator—this will let you quickly punch in your goals and get useful target numbers to determine how long your test should run and how large your audience should be.”
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Recommended pvalue threshold Report an error
“While the exact figure may vary, it’s recommended that most tests aim for a p-value of 5% or less to increase confidence that your data is reliable.”
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Significance level range Report an error
“In most cases, you’ll determine a significance level between 0.01 or 0.05, or 1-5%. This is a pretty common range for most significance levels.”
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Ab one variable Report an error
“And remember, for A/B testing, you’re only changing one variable at a time.”
1 fact read from this page is not shown because it could not be confirmed on the page as captured.
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