# `SKEWNESS_POP`

**Applies to:** ✅ Data 360 SQL ✅ Tableau Hyper API

Computes the population skewness of input values. Skewness measures the asymmetry of a distribution: positive values indicate a longer right tail, negative values indicate a longer left tail, and zero indicates a symmetric distribution.

## Syntax

```sql
skewness_pop(<expression>)
```

## Arguments

### Required

- `<expression>`: An expression of any numerical type.

## Returns

Returns a `double precision` value.

Returns NULL when fewer than three non-null input values are provided or when all non-null values are identical.

## Considerations

- Use `SKEWNESS_POP` when the data is the complete population of interest (for example, every order in a closed quarter). Use [`SKEWNESS_SAMP`](/docs/data/data-cloud-query-guide/references/dc-sql-reference/skewness-samp.md) when the data is a sample drawn from a larger population.
- Computes the Fisher–Pearson population coefficient of skewness, without bias correction.
- For large row counts, `SKEWNESS_POP` and `SKEWNESS_SAMP` converge.
- Ignores NULL inputs. Any NaN or infinite input propagates to a NaN result.

## Examples

### Calculate Population Skewness

Check whether last quarter's order totals are skewed toward a few large purchases.

```sql
SELECT skewness_pop(order_total) AS order_total_skew
FROM orders
WHERE order_quarter = '2026-Q1';
```

### Skewness by Group

Compare the asymmetry of score distributions across cohorts.

```sql
SELECT cohort, skewness_pop(score) AS score_skew
FROM exam_results
GROUP BY cohort;
```

## Related Documentation

- [SKEWNESS_SAMP](/docs/data/data-cloud-query-guide/references/dc-sql-reference/skewness-samp.md)
- [KURTOSIS](/docs/data/data-cloud-query-guide/references/dc-sql-reference/kurtosis.md)
- [STDDEV_POP](/docs/data/data-cloud-query-guide/references/dc-sql-reference/stddev-pop.md)
- [Aggregate Functions](/docs/data/data-cloud-query-guide/references/dc-sql-reference/aggregate.md)