# Source: https://docs.oxla.com/sql-reference/sql-functions/aggregate-functions/covar-pop.md

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# COVAR_POP()

## Overview

The `COVAR_POP()` aggregate function calculates the population covariance between two sets of number pairs.
This function measures how much two variables change together, providing insight into their linear relationship.

## Syntax

The syntax for this function is as follows:

```sql  theme={null}
COVAR_POP(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 uses the `COVAR_POP()` function to calculate the covariance between film length and rating:

```sql  theme={null}
SELECT
    COVAR_POP(length, rating) AS Covariance            
FROM film;
```

By running the query above, we will get the following output:

```sql  theme={null}
    covariance     
-------------------
 36.02768166089963
(1 row)
```