ECOMMERCE & MARKETING – CONVERION RATE OPTIMIATION (CRO) CALCULATOR
Sample Size Ab Test
A precise tool.
What is the Sample Size Ab Test & How does it work?
A/B testing is a statistical method used to compare two versions of a webpage, email, ad, etc., to determine which version performs better. The sample size required for an A/B test depends on the desired level of confidence and the minimum detectable effect (MDE) you want to identify.
The formula to calculate the required sample size for an A/B test is:
n = frac{2(z_{1-alpha/2} + z_{1-beta})^2 cdot p(1-p)}{(p_1 – p_2)^2}
n = required sample size per variant
z = Z-score for desired confidence level and power
p = estimated conversion rate
p_1, p_2 = expected conversion rates for the two variants
z = Z-score for desired confidence level and power
p = estimated conversion rate
p_1, p_2 = expected conversion rates for the two variants
Parameters
Result
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Frequently Asked Questions
What is the formula used to calculate sample size in an A/B test?
The formula used is n = [2(z_{1-alpha/2} + z_{1-beta})^2 cdot p(1-p)] / (p_1 – p_2)^2, where n is the required sample size per variant.
How do I determine the Z-score for my desired confidence level?
The Z-score corresponds to your chosen confidence level. For example, a 95% confidence level has a Z-score of approximately 1.96.
What is the minimum detectable effect (MDE) in an A/B test?
The MDE is the smallest difference in conversion rates between your two variants that you want to be able to detect with your test.
How does sample size affect the power of my A/B test?
A larger sample size increases the power of your test, making it more likely to detect a true effect if one exists.
What is the role of p in the sample size formula?
p represents the estimated conversion rate for your control group. It’s used to calculate the variance in your data.
How do I interpret the results from this calculator?
The result gives you the number of users needed per variant to achieve statistical significance with your chosen confidence level and MDE.
Can this calculator be used for non-binary outcomes?
This calculator is primarily designed for binary outcomes (e.g., success/failure). For other types of data, different calculations may be needed.
Results are for informational purposes only and do not constitute professional advice.