{"id":8925,"date":"2017-05-29T13:28:29","date_gmt":"2017-05-29T18:28:29","guid":{"rendered":"https:\/\/www.invespcro.com\/blog\/?p=8925"},"modified":"2024-09-17T14:46:13","modified_gmt":"2024-09-17T14:46:13","slug":"ab-testing-statistics-made-simple","status":"publish","type":"post","link":"https:\/\/www.invespcro.com\/blog\/ab-testing-statistics-made-simple\/","title":{"rendered":"A\/B Testing Statistics Made Simple"},"content":{"rendered":"Reading Time: <\/span> 11<\/span> minutes<\/span><\/span>

A\/B testing statistics can often seem overwhelming, but they are essential for making informed decisions.<\/p>\n

\u201cWhy do I need to learn about statistics to run an A\/B test?\u201d you may wonder, especially since the testing engine provides data to judge the statistical significance of the test, right?<\/span><\/p>\n

In fact, there are plenty of reasons to learn statistics.<\/span><\/p>\n

If you\u2019re conducting A\/B tests, you need a basic understanding of statistics to validate your tests and their results.<\/span><\/p>\n

Nobody wants to waste time, money, and effort on something useless. To use A\/B testing efficiently and effectively, you must understand it and the statistics behind it.<\/span><\/p>\n

Statistical hypothesis testing is at the core of A\/B testing<\/a>. Sounds exciting, huh?<\/span><\/p>\n

No worries, you won\u2019t be grinding through statistics and calculations\u2014this is all done automatically. However, you should know the key concepts and how to interpret test results to make them meaningful.<\/span><\/p>\n

Let\u2019s start by exploring some of the basics.<\/span><\/p>\n

A\/B Testing Key Terminology<\/span><\/h2>\n

1. Variants (Control & Treatment)<\/span><\/h3>\n

In A\/B testing, “variants” are the two versions of something you’re testing.\u00a0<\/span><\/p>\n

These are usually called Control and Treatment:<\/b><\/p>\n