# Hypothesis Tests

Canonical: https://manyspace.aporia.systems/topics/hypothesis-tests-mth-stats-217
Updated: 2026-10-13

Mathematics · Statistics · MTH-STATS-217

- Difficulty: 3 / 5
- Importance: 5 / 5
- Study time: 4–7.5 h

null/alternative, p-values, errors, power, one- and two-sample tests

## Why it matters

Turning data into decisions under uncertainty; the quantitative backbone of business analytics, science and ML evaluation.

## Where it is used

A/B testing, market research, QC, clinical trials, customer analytics, experimentation platforms.

## How you know you have learned it

Solve ≥10 representative problems with ≥80% adjusted accuracy.

## What you need first

- [Sample Spaces & Events](https://manyspace.aporia.systems/topics/sample-spaces-events-mth-prob-196) (required)
- [Confidence Intervals](https://manyspace.aporia.systems/topics/confidence-intervals-mth-stats-216) (required)

## What it opens

- [Experiment Design](https://manyspace.aporia.systems/topics/experiment-design-ent-growth-106)
- [A/B Testing Practice](https://manyspace.aporia.systems/topics/a-b-testing-practice-ent-growth-108)
- [Linear Regression](https://manyspace.aporia.systems/topics/linear-regression-mth-stats-220)
- [Statistical Significance and Confidence Intervals for Evaluation](https://manyspace.aporia.systems/topics/statistical-significance-and-confidence-intervals-for-evaluation-aiml-eval-012)

## Resources

- Statistics (Freedman, Pisani & Purves) — Freedman, Pisani & Purves
- Statistics (Freedman, Pisani & Purves) — Freedman, Pisani & Purves
- The Elements of Statistical Learning — Hastie, Tibshirani & Friedman