> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oxla.com/llms.txt
> Use this file to discover all available pages before exploring further.

# COVAR_SAMP

## Overview

The `COVAR_SAMP()` aggregate function calculates the sample covariance between two sets of number pairs. This function measures how changes in one variable relate linearly to changes in another variable within a sample dataset.

## Syntax

The syntax for this function is as follows:

```sql theme={null}
COVAR_SAMP(y, x)
```

## Parameters

* `y`: variable being predicted
* `x`: variable used for prediction

## Example

For the needs of this section, we're going to use a simplified version of the `film` table from the Pagila database, containing only the `title`, `length` and `rating` columns. The complete schema for the `film` table can be found on the
<a href="https://www.postgresql.org/ftp/projects/pgFoundry/dbsamples/pagila/pagila/" target="_blank">Pagila</a> database website.

```sql theme={null}
DROP TABLE IF EXISTS film;
CREATE TABLE film (
  title text NOT NULL,
  length int,
  rating int
);
INSERT INTO film(title, length, rating) VALUES
  ('ATTRACTION NEWTON', 83, 5),
  ('CHRISTMAS MOONSHINE', 150, 7),
  ('DANGEROUS UPTOWN', 121, 4),
  ('KILL BROTHERHOOD', 54, 3),
  ('HALLOWEEN NUTS', 47, 5),
  ('HOURS RAGE', 122, 7),
  ('PIANIST OUTFIELD', 136, 7),
  ('PICKUP DRIVING', 77, 3),
  ('INDEPENDENCE HOTEL', 157, 7),
  ('PRIVATE DROP', 106, 4),
  ('SAINTS BRIDE', 125, 3),
  ('FOREVER CANDIDATE', 131, 7),
  ('MILLION ACE', 142, 5),
  ('SLEEPY JAPANESE', 137, 4),
  ('WRATH MILE', 176, 7),
  ('YOUTH KICK', 179, 7),
  ('CLOCKWORK PARADISE', 143, 5);
```

The query below query uses the `COVAR_SAMP()` function to calculate the sample covariance between film `length` and `rating` where `rating` is greater than or equal to 4:

```sql theme={null}
SELECT
    COVAR_SAMP(length, rating) AS SampleCovariance
FROM film
WHERE rating >= 4;
```

By running the above query will get the following output:

```sql theme={null}
  samplecovariance  
--------------------
 23.087912087912066
(1 row)
```