So in this article, I will walk you through what p-values are, how they’re used in the world of hypothesis testing (e.g. A/B testing), and how to interpret them.

The margin of error is an important statistical concept that helps you avoid over-generalizing the results of a survey or poll. In this article I use charts to help make margin of error easier to understand.

If you've ever dabbled in the world of statistics, you might've heard a whisper or two about the margin of error, sometimes abbreviated as MoE. But what on earth does it mean, and why does it matter?

This is a repost of an article originally written and published by Peter Borden, and which was published on the blog of the now defunct social analytics company, SumAll. I came across this article back when Peter wrote it in 2014, and I found it to be an absolutely essential part of the discourse in the A/B testing industry. And so I wanted to re-publish the original article, since the original link is now dead, to help preserve its educational value for anyone interested in learning about A/B testing.