---
title: Type I Error - Definition & Examples | RGM® Glossary
url: https://realgrowthmatters.com/glossary/type-i-error/
updated: 2026-06-10
source_html: https://realgrowthmatters.com/glossary/type-i-error/
---

Growth Glossary — Definition

SHT TYPE-I-ERROR

# Type I Error

Rejecting true null hypothesis (false positive). A working definition from the RGM marketing glossary.

Rejecting true null hypothesis (false positive).

Term
:   Type I Error

Field
:   Statistics & Analytics

Category
:   Statistics & Analytics

## What the term covers

Read that twice.Treat Type I Error as an analytical concept with a clear scope. Two people using the term should mean the same thing.

Rejecting true null hypothesis (false positive).

In Statistics & Analytics, Type I Error names an analytical concept. Pin the meaning down early and the strategy stays coherent.

## How it operates

Pick one definition.Type I Error produces value through how it is applied. Change the inputs and the right use of it changes too.

Think of Type I Error as context-bound. A small shop reads it simply; an enterprise reads it with more nuance. That is normal -- Type I Error is shaped by audience and channel mix. Read Type I Error without care and the plan wobbles; be precise and the read holds.

One rule always holds. Settle the scope of Type I Error up front, then build the plan. Get it backwards and Type I Error becomes a word everyone uses and no one shares. Worth a slow read.

## When it matters

Hold that thought.Bring Type I Error in when a live call depends on it. With no decision on the table, it stays background.

Type I Error matters at the point of a decision. In statistics & analytics, three moments come up again and again. Outside them, Type I Error is reference material.

1. **Setting budget.** Type I Error clarifies which budget line deserves more.
2. **Choosing a metric.** Type I Error checks that the figure is not just noise.
3. **Comparing options.** Type I Error adjusts a compare so the gap is honest.

## A worked example

Keep this in mind.The walk-through runs Type I Error through work modeled on Booking.com, so the concept meets real constraints.

Consider Booking.com. Running a sample-size correction, the team put Type I Error at the center of the call. With a clean baseline and one fixed definition of Type I Error, they read what moved: 3 of 10 tests stopped being called too early. The discipline is the lesson.

The numbers behind Type I Error -- illustrative only, RGM analysis

| Stage | The step taken | Why it mattered |
| Baseline | Took a before reading on Type I Error. | A reference to judge against. |
| Define | Locked the scope of Type I Error so it stayed stable. | No room for scope drift. |
| Act | A sample-size correction — one variable. | One change, a clean read. |
| Result | 3 of 10 tests stopped being called too early | A decision the data earned. |

Treat the Type I Error figures as illustrative, labeled RGM analysis. Reuse the sequence, not the digits.

## Common mistakes

Read that twice.Teams slip on Type I Error in four familiar ways. Each makes a soft assumption look like a precise number.

- **One-size thinking.** Using Type I Error flat across every segment. The right cut differs by channel and margin.
- **Bare numbers.** Showing Type I Error on its own. Context is what makes it readable.
- **Chasing the word.** Optimizing Type I Error for its own sake. Check it tracks a real outcome.
- **Bad compares.** Benchmarking Type I Error with no adjustment. Account for the model differences first.

## Common questions

What is Type I Error?

Rejecting true null hypothesis (false positive). Agree the scope of Type I Error before the planning starts.

What makes Type I Error worth knowing?

Type I Error shows up in budget reviews and channel reporting. Use it loosely and teams pull apart; use it precisely and the numbers line up.

Where does Type I Error get used?

Type I Error supports a real choice: where money goes, what gets measured, which option wins. The Booking.com case traces it.

Where do teams slip up on Type I Error?

Treating Type I Error as one blanket rule and reporting it with no baseline. Both hide a soft assumption.

Where can I go deeper on Type I Error?

Start with the related terms below, then read the guide on CAC payback periods, plus marketing attribution models.

What is Type I Error?
:   Rejecting true null hypothesis (false positive). Agree the scope of Type I Error before the planning starts.

What makes Type I Error worth knowing?
:   Type I Error shows up in budget reviews and channel reporting. Use it loosely and teams pull apart; use it precisely and the numbers line up.

Where does Type I Error get used?
:   Type I Error supports a real choice: where money goes, what gets measured, which option wins. The Booking.com case traces it.

### Go deeper

### Related terms