State of the art statistics for A/B tests
Address the leading reason for failure in online experimentation - poor use of statistical methods.
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A/B Testing Hub
A/B testing statistics done right
Smart and rigorous statistics are often the missing driver of success for CRO & UX teams.
Free online tools are too simple, inefficient, and invite malpractice. Many others appear statistically sound yet make compromises with the very essence of what that means. Claims of tests optimal for your business are made while failing to take any business metrics as input.
The A/B testing hub changes all that and helps you make the most of your online A/B tests.More on stats for success
“Unrivaled statistical rigor combined with a unique method for planning tests for optimal business returns”
Founder of Analytics Toolkit and Author of Statistical Methods in Online A/B Testing
Knowing your way around stats?
You can use any of our statistical tools as a standalone calculator as well:
Plan your A/B tests for optimal balance of risk & reward.
Robust p-value and confidence interval calculation.
Estimate the sample size requirement of an A/B test.
Estimate the false negative rate & sensitivity of a test.
Adjust p-values when working with multiple test KPIs.
Average or cumulative results of multiple experiments.
Check your experiments for sample ratio mismatch.
Supported API connections
Analytics Toolkit has been used by thousands of businesses
“The value added to our agency by these tools is tremendous. I would say it provides Inflow with the best bang for the buck out of any tool we pay for.“
Director of Inbound Services, InFlow
Level up your knowledge of A/B testing statistics
All our content is by Georgi Georgiev who literally wrote the book on statistics in online A/B testing!Start learning
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