Question 1

What is a calculator for sequential A/B test analysis and why is it needed?

Accepted Answer

The calculator for sequential A/B test analysis is a tool that helps determine the optimal moment to stop an experiment based on statistical data. It takes into account the baseline conversion, minimum detectable effect, statistical power, and significance level to help you make an informed decision about continuing or stopping the test.

Question 2

How does the calculator for sequential A/B test analysis work?

Accepted Answer

The calculator uses statistical methods to estimate the minimum sample size based on baseline conversion, minimum detectable effect, statistical power, and significance level. It shows when the experiment can be stopped.

Question 3

What is the difference between absolute and relative effect?

Accepted Answer

Absolute effect is a percentage difference (e.g., a 5% increase in conversion). Relative effect is a percentage change from the baseline conversion (e.g., a 25% increase from a 20% baseline conversion).

Question 4

How to adjust statistical power and significance level?

Accepted Answer

Statistical power (60-95%) determines the probability of detecting an effect if it exists. The significance level (1-10%) determines the probability of a false positive. Higher power requires a larger sample size. You can adjust the statistical power and significance level in the calculator.

Question 5

When should sequential testing be used?

Accepted Answer

Sequential testing is ideal for A/B tests with high observation costs, where it is important to save resources. It is also useful for quickly obtaining results in marketing campaigns.

Question 6

What is Type I error (false positive) and Type II error (false negative) in A/B testing?

Accepted Answer

A Type I error (alpha) is when you reject a true null hypothesis (conclude there's a difference when there isn't). A Type II error (beta) is when you fail to reject a false null hypothesis (conclude there's no difference when there is).

Question 7

Is sequential sampling suitable for all A/B tests?

Accepted Answer

Sequential sampling is particularly useful when the cost of each observation is high or when you want to get results faster. However, it requires constant monitoring of results, which can be more challenging to implement than a fixed-size test.

Question 8

What is 'baseline conversion' in the context of this calculator?

Accepted Answer

Baseline conversion is the current or expected conversion rate of your control group (the original variant). It's the reference point from which you measure the potential impact of your new variant (the test group).

A/B testing Calculator: Sequential Sampling

Sequential results

Save result

Sequential Sampling Calculator for A/B Testing

Frequently Asked Questions (FAQ)

Rate this tool

Useful Instruments

Sample Size Calculator

Chi-Square Test

Two-Sample T-Test

Sample Size Calculation for Sequential Testing

Statistical Power and Significance Level Consideration

Resource Optimization for A/B Tests