# quantileSeq() Function & Examples

Use the quantileSeq() statistics function in Calcul.io. Review its syntax, edit working examples, understand the result, and explore related math functions.

## quantileSeq

#### quantileSeq(A, prob[, sorted])

#### quantileSeq(A, [prob1, prob2, ...][, sorted])

#### quantileSeq(A, N[, sorted])

Try it yourself:

```calculio
quantileSeq([3, -1, 5, 7], 0.5)
quantileSeq([3, -1, 5, 7], [1/3, 2/3])
quantileSeq([3, -1, 5, 7], 2)
quantileSeq([-1, 3, 5, 7], 0.5, true)
```

[mean](https://calcul.io/function/mean/index.md)

[median](https://calcul.io/function/median/index.md)

[min](https://calcul.io/function/min/index.md)

[max](https://calcul.io/function/max/index.md)

[prod](https://calcul.io/function/prod/index.md)

[std](https://calcul.io/function/std/index.md)

[sum](https://calcul.io/function/sum/index.md)

[variance](https://calcul.io/function/variance/index.md)

---

## quantileSeq(): Quantiles from Ordered Data

**quantileSeq()** computes quantiles from a data sequence, identifying values below which a chosen fraction of observations falls. Quartiles and percentiles are common examples.

## Prepare data first

Quantiles depend on ordering and interpolation conventions. Sort data with [sort()](https://calcul.io/function/sort/index.md) when needed, and document the selected probability and method. Use [median()](https://calcul.io/function/median/index.md) for the 50th-percentile concept and [mean()](https://calcul.io/function/mean/index.md) for an average, which answers a different question.

Ensure the sequence is nonempty and that probabilities are within the accepted range. Extreme quantiles can be sensitive to small samples; inspect count with [size()](https://calcul.io/function/size/index.md) and outliers with [min()](https://calcul.io/function/min/index.md) or [max()](https://calcul.io/function/max/index.md).

[All functions](https://calcul.io/functions/index.md)