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  Stan combines powerful statistical modeling capabilities with user-friendly interfaces, an active community, and a commitment to open-source development.

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# Stan: Software for Bayesian Data Analysis

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### Bayesian Modeling

Stan enables sophisticated statistical modeling using Bayesian inference, allowing for more accurate and interpretable results in complex data scenarios.

### Flexible and Scalable

Stan's probabilistic programming language is suitable for a wide range of applications, from simple linear regression to multi-level models and time-series analysis.

### Multi-Language, Cross-Platform Toolkit

Interfaces for Python, Julia, R, and the Unix shell make it easy to use Stan in any programming environment,
on  laptops, clusters, or in the cloud.  A rich ecosystem of tools for validation and visualization support
decision-making and communication.
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```{.stan filename="bernoulli.stan"}
data {
  int<lower=0> N;
  array[N] int<lower=0, upper=1> y;
}
parameters {
  real<lower=0, upper=1> theta;
}
model {
  // uniform prior on interval 0,1
  theta ~ beta(1, 1);
  y ~ bernoulli(theta);
}
```

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### Community Resources
* The Stan [forums](https://discourse.mc-stan.org) provide support for all user levels and topics, from installing software, to writing Stan programs, to advanced Bayesian modeling techniques and methodology.

* Stan's [documentation](https://mc-stan.org/docs), [tutorials](learn-stan/tutorials.qmd), and [case studies](learn-stan/case-studies.qmd) help users learn and use Stan effectively in their own projects.
The [Prior Choice Recommendations](https://github.com/stan-dev/stan/wiki/Prior-Choice-Recommendations) wiki page provides guidance on appropriate priors for use with Stan.

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### Developer Resources
* The [Stan Developer Wiki](https://github.com/stan-dev/stan/wiki)

* The [Stan Forums Developers category](https://discourse.mc-stan.org/c/stan-dev/10)

* The Stan slack channel [mc-stan.slack.com](https://join.slack.com/t/mc-stan/shared_invite/zt-1le4ebi4m-UMtiOkJb4gcS16qz2wIYCw)
is for informal developer discussions.

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