B
Evidence Grade B
Graded
accuracy verified by the review judge
Safe to Cite
Current
70%
70% -- share of ab tests underpowered for A/B tests (meta-analysis of 115 tests) (2026)
A meta-analysis of 115 real A/B tests found that 70% were underpowered.
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Lighthouse Research Team
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Evidence graded
Value
70%
Unit
Percentage
Data Vintage
2026
Entity
Sample Size
115
Evidence Quality
B
Strong, reliable evidence
Sourced from a well-regarded research firm or industry leader with transparent methodology and a reasonably large sample.
Single source - not yet corroborated
Score breakdown
Extraction
50
Source Trust
60
Citation Chain
20
Independence
30
Methodology
45
Freshness
95
Source
Analytics Toolkit
Primary
Tier C
https://kirro.io/ab-test-sample-size-formula ↗
Source Article
A/B test sample size formula explained simply
The A/B test sample size formula is:
n = (Zα/2 + Zβ)² × [p₁(1−p₁) + p₂(1−p₂)] / (p₁−p₂)²
If that looks like gibberish, you’re not alone. Most articles either throw this formula at you with zero explanation, or skip it and say “just use a calculator.”
This guide does both. We’ll break down every piec…
Original Research
Analytics Toolkit
· Original study ↗
Methodology
Meta-analysis of 115 real A/B tests, cited by kirro.io
Methodology documented
Segmentation
Industrymarketing
Cite this stat
Plain Text
A/B tests (meta-analysis of 115 tests): 70% share of ab tests underpowered. Source: Analytics Toolkit (2026). Via Lighthouse Intelligence -- https://lighthousedata.io/data/ab-tests-underpowered-115
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<blockquote cite="https://lighthousedata.io/data/ab-tests-underpowered-115" style="border-left:3px solid #2563eb;padding:12px 16px;margin:16px 0;font-family:system-ui,sans-serif;background:#f0f4ff;"><strong>70%</strong> -- share of ab tests underpowered for A/B tests (meta-analysis of 115 tests)<br><small>Source: Analytics Toolkit (2026) · <a href="https://lighthousedata.io/data/ab-tests-underpowered-115" target="_blank" rel="noopener">Lighthouse Intelligence</a></small></blockquote>
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