A/B Split Test Statistical Significance Calculator
Calculate two tailed Z score, p value, relative conversion lift, and statistical confidence intervals (90%, 95%, 99%) between Control (Variant A) and…
How to Use the A/B Split Test Statistical Significance Calculator
- 1 Enter Total Visitors and Conversions for Control Variant A.
- 2 Enter Total Visitors and Conversions for Treatment Variant B.
- 3 Review relative conversion lift percentage (%), two tailed Z score, and p value.
- 4 Check the automated decision banner: "Statistically Significant (>95%)" vs "Inconclusive / Keep Testing".
Methodology & Algorithmic Standards
Implements two-proportion pooled Z-test: $Z = \frac{p_B - p_A}{\sqrt{P(1-P)(1/n_A + 1/n_B)}}$ where $P$ is the pooled sample conversion rate. Computes Gaussian cumulative distribution function for two tailed p-values.
Frequently Asked Questions
What statistical confidence threshold should I aim for? ▼
The industry standard benchmark for CRO is 95% confidence (p < 0.05), which indicates only a 5% chance the observed conversion lift was due to random sampling variance.
Why should I not stop an A/B test too early? ▼
Stopping a test as soon as it reaches 95% significance (known as "peeking bias") dramatically inflates false positive error rates. Tests should run for at least 1 to 2 full business cycles.
Can I export this experiment report into Olevx Notepad? ▼
Yes! Click "Open in Notepad" to create a structured marketing experiment summary.
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