Interactive A/B Testing Calculator

Adjust the parameters below to simulate different experiment outcomes and see real-time Power Analysis.

Control Rate (p₁)

Test Rate (p₂)

Alpha (α)

Beta (β)

Control Sample (n₁)

Test Sample (n₂)

Control Conv. (x₁)

Test Conv. (x₂)

1. Power Analysis

The Concept: Before trusting the result, we must ensure we have enough data. Power analysis calculates the minimum sample size required to detect the effect you specified.

The Formula $$n = \frac{(Z_{1-\alpha/2} + Z_{1-\beta})^2 \cdot p(1-p)}{(p_2 - p_1)^2}$$

Live Calculation

2. Test Execution Results

Standard Error $$se = \sqrt{p(1-p)\left(\frac{1}{n_1}+\frac{1}{n_2}\right)}$$

Result

Z-Score $$z = \frac{p_2 - p_1}{se}$$

Result

Lift Percentage $$\text{lift \%} = \frac{p_2 - p_1}{p_1}$$

Result