ClickHouse/docs/en/sql-reference/aggregate-functions/reference/corr.md

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---
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slug: /en/sql-reference/aggregate-functions/reference/corr
sidebar_position: 117
---
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# corr
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Calculates the [Pearson correlation coefficient](https://en.wikipedia.org/wiki/Pearson_correlation_coefficient):
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{\sqrt{\Sigma{(x - \bar{x})^2} * \Sigma{(y - \bar{y})^2}}}
$$
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:::note
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This function uses a numerically unstable algorithm. If you need [numerical stability](https://en.wikipedia.org/wiki/Numerical_stability) in calculations, use the [`corrStable`](../reference/corrstable.md) function. It is slower but provides a more accurate result.
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:::
**Syntax**
```sql
corr(x, y)
```
**Arguments**
- `x` — first variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
- `y` — second variable. [(U)Int*](../../data-types/int-uint.md), [Float*](../../data-types/float.md), [Decimal](../../data-types/decimal.md).
**Returned Value**
- The Pearson correlation coefficient. [Float64](../../data-types/float.md).
**Example**
Query:
```sql
DROP TABLE IF EXISTS series;
CREATE TABLE series
(
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i UInt32,
x_value Float64,
y_value Float64
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)
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ENGINE = Memory;
INSERT INTO series(i, x_value, y_value) VALUES (1, 5.6, -4.4),(2, -9.6, 3),(3, -1.3, -4),(4, 5.3, 9.7),(5, 4.4, 0.037),(6, -8.6, -7.8),(7, 5.1, 9.3),(8, 7.9, -3.6),(9, -8.2, 0.62),(10, -3, 7.3);
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```
```sql
SELECT corr(x_value, y_value)
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FROM series;
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```
Result:
```response
┌─corr(x_value, y_value)─┐
│ 0.1730265755453256 │
└────────────────────────┘
```