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# A/B Test Calculator Online

The A/B Test Calculator helps users evaluate the effectiveness of two different variants, A and B, by comparing conversion rates or other metrics. This tool is invaluable for anyone looking to optimize their website, campaign, or product without needing deep statistical knowledge. It provides a clear, quantifiable way to determine which variant yields better performance.

## Formula of A/B Test Calculator Online

The accuracy of an A/B test hinges on several statistical calculations:

• Conversion rate for variant A: CR_A = Conversions_A / Visitors_A
• Conversion rate for variant B: CR_B = Conversions_B / Visitors_B
• Pooled Conversion Rate: CR_pooled = (Conversions_A + Conversions_B) / (Visitors_A + Visitors_B)
• Standard Error: SE = sqrt(CR_pooled * (1 – CR_pooled) * (1 / Visitors_A + 1 / Visitors_B))
• Z-Score: Z = (CR_A – CR_B) / SE
• P-Value: Determined by the Z-score to assess the significance of the results.

Understanding these calculations will help you accurately interpret the results from the A/B Test Calculator.

## Table of General Terms and Useful Conversions

Here’s a table that includes typical values needed when conducting an A/B test. This table serves as a quick reference to understand various metrics without calculating each time manually.

## Example of A/B Test Calculator Online

Imagine you are testing two different designs for a website’s landing page. Variant A receives 200 conversions from 4,000 visitors, and Variant B receives 240 conversions from 4,000 visitors. Here’s how you’d use the A/B Test Calculator to analyze which variant performs better:

1. Calculate the conversion rate for each variant:
• CR_A = 200 / 4000 = 0.05 (5%)
• CR_B = 240 / 4000 = 0.06 (6%)
2. Calculate the pooled conversion rate:
• CR_pooled = (200 + 240) / (4000 + 4000) = 440 / 8000 = 0.055 (5.5%)
3. Calculate the standard error:
• SE = sqrt(0.055 * (1 – 0.055) * (1/4000 + 1/4000)) = sqrt(0.055 * 0.945 * 0.0005) = 0.0051
4. Calculate the Z-Score:
• Z = (0.05 – 0.06) / 0.0051 = -0.0196 / 0.0051 = -1.96
5. Reference the Z-score in a standard normal distribution table to find the p-value. If the p-value is less than 0.05, the result is considered statistically significant, indicating that Variant B performs better than Variant A.

## Most Common FAQs

What is A/B Testing?

A/B testing is a method to compare two versions of a single variable to determine which one performs better.

How accurate is the A/B Test Calculator?

It is highly accurate, provided the input data is correct. It uses standard statistical methods to ensure reliability.

Can I use this calculator for any type of A/B testing?

Yes, it’s versatile and can be used across different domains wherever A/B testing is applicable.