# Tag Archives: statistical power

## Underpowered A/B Tests – Confusions, Myths, and Reality

In recent years a lot more CRO & A/B testing practitioners have started paying more attention to the statistical power of their online experiments, at least based on my observations. While this a positive development for which I hope I had contributed somewhat, it comes with the inevitable confusions and misunderstandings surrounding a complex concept […] Read More…

## A/B Testing with a Small Sample Size

The question “How to test if my website has a small number of users” comes up frequently when I chat to people about statistics in A/B testing, online and offline alike. There are different opinions on the topic ranging from altering the significance threshold, statistical power or the minimum effect of interest all the way […] Read More…

Posted in A/B Testing, Conversion Optimization, Statistics | | Comments closed

## The A/B Testing Guide to Surviving on a Deserted Island

The secluded and isolated deserted island setting has been used as the stage for many hypothetical explanations in economics and philosophy with the scarcity of things that can be developed as resources being a central feature. Scarcity and the need to keep risk low while aiming to improve one’s situation is what make it a […] Read More…

## Analysis of 115 A/B Tests: Average Lift is 4%, Most Lack Statistical Power

What can you learn from 115 publicly available A/B tests? Usually, not much, since in most cases you would be looking at case studies with very basic data about what was tested and the outcome of the A/B test. Confidence intervals, p-values and other measurements of uncertainty will often be missing, and when present they […] Read More…

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## Statistical Significance in A/B Testing – a Complete Guide

The concept of statistical significance is central to planning, executing and evaluating A/B (and multivariate) tests, but at the same time it is the most misunderstood and misused statistical tool in internet marketing, conversion optimization, landing page optimization, and user testing. This is not my first take on the topic, but it is my best […] Read More…

## Efficient AB Testing with the AGILE Statistical Method

Don’t we all want to run tests as quickly as possible, reaching results as conclusive and as certain as possible? Don’t we all want to minimize the number of users we send to an inferior variant and to implement a variant with positive lift as quickly as possible? Don’t we all want to get rid of […] Read More…