# MonteCarloTesting.jl — Statistical hypothesis testing via Monte Carlo simulations

**URL:** <https://discourse.julialang.org/t/montecarlotesting-jl-statistical-hypothesis-testing-via-monte-carlo-simulations/96762>\
**Category:** Package Announcements\
**Created:** [March 29, 2023, 9:02am UTC](https://discourse.julialang.org/t/montecarlotesting-jl-statistical-hypothesis-testing-via-monte-carlo-simulations/96762 "2023-03-29T09:02:40Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![aplavin](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/aplavin/32/222056_2.png) [@aplavin](https://discourse.julialang.org/u/aplavin)\
**Post date:** [March 29, 2023, 9:02am UTC](https://discourse.julialang.org/t/montecarlotesting-jl-statistical-hypothesis-testing-via-monte-carlo-simulations/96762/1 "2023-03-29T09:02:41Z")

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[MonteCarloTesting.jl](https://gitlab.com/aplavin/MonteCarloTesting.jl) (registered in General) performs hypothesis testing based on simulations, even when no analytic solutions are available. The only requirement is to be able to generate synthetic data under the null hypothesis.

Main pieces of functionality:

- convenience containers for Monte-Carlo simulations,
- confidence intervals on p-values,
- performing parameter scans,
- and properly correcting for multiple trials.

![image](https://global.discourse-cdn.com/julialang/original/3X/2/f/2fa7da249f3767d59902242f1e87b3f22a3675a5.png)

See the [walkthrough](https://aplavin.github.io/MonteCarloTesting.jl/test/examples.html) with plots and explanations as a Pluto notebook.