---
title: Hypothesis Test Selector
description: "From “I think” to “the data proves”. This guide walks you from your data type to the right statistical test, and tells you how to read the p-value. Watch the short video, then work with the toolkit PDF: it explains…"
url: "https://skillagility.com/en/resources/hypothesis-test-selector/"
updated: "2026-10-11"
category: 03 ANALYZE
---

# Hypothesis Test Selector

From “I think” to “the data proves”. This guide walks you from your data type to the right statistical test, and tells you how to read the p-value. 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.

[Hypothesis-Test-Selector_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%2FHypothesis-Test-Selector_Toolkit_EN.pdf#key=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)

## Hypothesis Test Selector in short

1. **State H0 and H1.** H0: the cause has no effect. H1: it does.
2. **Check the data type.** Continuous (time, weight) or discrete (pass/fail, category)?
3. **Name the comparison.** Against a target, two groups, before/after, three or more groups? Means, variation or proportions?
4. **Check normality.** Before a t-Test or ANOVA. Not normal? Use a non-parametric test.
5. **Run and decide.** p < 0.05: reject H0, the cause is real. p ≥ 0.05: not proven.

Key points

- Start from H0: no effect.
- Data type and comparison pick the test.
- p < 0.05: the cause is real.
- Check normality before t-Test or ANOVA.

**Excel tool:** [Hypothesis Tests (.xlsx)](https://skillagility.com/wp-content/uploads/2026/10/B303_Hypothesis-Tests_EN.xlsx)

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