---
title: What is Sequential testing?
url: https://markin.ai/glossary/sequential-testing
category: Experimentation and causality
aliases: Always-valid inference
---

# Sequential testing

> Sequential testing allows results to be monitored continuously and stopped early without inflating false positives, using always-valid confidence intervals instead of a single fixed-horizon check. It formalises the peeking that teams do anyway.

## Why it matters for ARPU

It is what makes continuous decisioning statistically legitimate: decisions can be made as soon as the evidence supports them, not only on a scheduled read-out date.

## Related terms

- [A/B test](https://markin.ai/glossary/ab-test), An A/B test randomly assigns customers to two or more variants and compares a pre-declared metric between them.
- [Statistical power](https://markin.ai/glossary/statistical-power), Statistical power is the probability that a test detects an effect of a given size when that effect is real.
- [Multi-armed bandit](https://markin.ai/glossary/multi-armed-bandit), A multi-armed bandit allocates traffic adaptively toward variants that are performing well while continuing to sample the others.
- [Experiment](https://markin.ai/glossary/experiment), An experiment is a controlled release of a candidate action against a randomised holdout, sized in advance so the result can distinguish a real effect from noise.

## Go deeper

- [Experimentation vs continuous decisioning](https://markin.ai/compare/experimentation-vs-continuous-decisioning), Stopping rules for a running loop.
- [Growth optimization](https://markin.ai/solutions/growth-optimization), Continuous read-outs.

Source: https://markin.ai/glossary/sequential-testing