---
title: Sample Size
description: "How much data is enough? The sample size formula gives you a clear answer, so you collect neither too little nor too much. Watch the short video, then work with the toolkit PDF: it explains the method, shows a worked…"
url: "https://skillagility.com/en/resources/sample-size/"
updated: "2026-10-07"
category: 02 MEASURE
---

# Sample Size

How much data is enough? The sample size formula gives you a clear answer, so you collect neither too little nor too much. Watch the short video, then work with the toolkit PDF: it explains the method, shows a worked example and gives you a blank template to fill in.

Tool video

The short tool video will appear here.

[Sample-Size_Toolkit_EN](https://skillagility.com/wp-content/plugins/embedpress/assets/pdf/web/viewer.html?&file=https%3A%2F%2Fskillagility.com%2Fwp-content%2Fuploads%2F2026%2F10%2FSample-Size_Toolkit_EN.pdf#key=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)

## Sample Size in short

1. **Choose the confidence level.** 95 % is the usual standard. Then Z = 1.96.
2. **Set the margin of error.** How close must the result be? For example ± 5 percentage points.
3. **Estimate p.** Use an earlier rate if you have one, otherwise 0.5 for the safe maximum.
4. **Calculate n and round up.** Put the numbers into the formula and always round up.
5. **Plan a random sample.** Spread the sample over days, shifts and products so it represents the whole.

Key points

- More certainty or precision needs more data.
- 95 % confidence: Z = 1.96.
- Unknown share: use p = 0.5.
- The sample must be random and representative.

**Related tools:** [Data Collection Plan](https://skillagility.com/en/resources/data-collection-plan/) · [Baseline & Sigma Level](https://skillagility.com/en/resources/baseline-sigma-level/)