Why Type I and Type II Errors Matter

A/B testing is an essential component of large scale online services today. So essential, that every online business worth mentioning has been doing it for the last 10 years. A/B testing is also used in email marketing by all major online retailers. The Obama for America data science team received a lot of press coverage for leveraging data science, especially A/B testing during the presidential campaign.

null hypothesis and alternative hypothesis testing outcomes

Here is an interesting article on this topic along with a data science bootcamp that teaches a/b testing and statistical analysis.

If you have been involved in anything related to A/B testing (online experimentation) on UI, relevance or email marketing, chances are that you have heard of Type I and Type II errors. The usage of these terms is very common but a good understanding of them are not.

I have seen illustrations as simple as this.

Examples of Type I and Type II Errors

I intend to share two great examples I recently read that will help you remember this very important concept in hypothesis testing.

TYPE I ERROR: An alarm without a fire.
TYPE II ERROR: A fire without an alarm.

Every cook knows how to avoid Type I Error – just remove the batteries. Unfortunately, this increases the incidences of Type II error. 🙂

Reducing the chances of Type II error would mean making the alarm hypersensitive, which in turn would increase the chances of Type I error.

Another way to remember this is by recalling the story of the Boy Who Cried Wolf.

tye 1 and type 2 errors data science blog

Null Hypothesis: There is no wolf.
Alternate Hypothesis: There is a wolf.

Villagers believing the boy when there was no wolf (Rejecting null hypothesis incorrectly): Type I Error
Villagers not believing the boy when there actually was a wolf (Rejecting alternate hypothesis incorrectly): Type II Error


The purpose of the post is not to explain type I and type II errors. If this is the first time you are hearing about these terms, here is the Wikipedia entry: Type I and Type II Error.

Type I and Type II Errors | Smoke Detector and The Boy Who Cried Wolf