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- Astrostatistics Tools (`astropy.stats`)

# Astrostatistics Tools (`astropy.stats`)

## Introduction

The `astropy.stats` package holds statistical functions or algorithms used in astronomy and astropy.

## Getting Started

The current tools are fairly self-contained, and include relevant examples in their docstrings. For example, see `sigma_clip`.

## See Also

- `scipy.stats`

    This scipy package contains a variety of useful statistical functions and classes. The functionality in `astropy.stats` is intended to supplement this, not replace it.

## Reference/API

### astropy.stats Module

This subpackage contains statistical tools provided for or used by Astropy.

While the `scipy.stats` package contains a wide range of statistical tools, it is a general-purpose package, and is missing some that are particularly useful to astronomy or are used in an atypical way in astronomy. This package is intended to provide such functionality, but not to replace `scipy.stats` if its implementation satisfies astronomers’ needs.

#### Functions

`binned_binom_proportion`(x, success[, bins, ...]) | Binomial proportion and confidence interval in bins of a continuous variable `x`.
`binom_conf_interval`(k, n[, conf, interval]) | Binomial proportion confidence interval given k successes, n trials.
`biweight_location`(a[, c, M]) | Compute the biweight location for an array Returns the biweight location for the array elements.
`biweight_midvariance`(a[, c, M]) | Compute the biweight midvariance for an array Returns the biweight midvariance for the array elements.
`bootstrap`(data[, bootnum, samples, bootfunc]) | Performs bootstrap resampling on numpy arrays.
`median_absolute_deviation`(a[, axis]) | Compute the median absolute deviation Returns the median absolute deviation of the array elements.
`sigma_clip`(data[, sig, iters, cenfunc, ...]) | Perform sigma-clipping on the provided data.
`signal_to_noise_oir_ccd`(t, source_eps, ...) | Computes the signal to noise ratio for source being observed in the optical/IR using a CCD.