PERCENTILEINC

Calculates the percentile of a dataset to find the value below which a given percentage of data falls.

The PERCENTILEINC function returns the k-th percentile of a dataset using the inclusive method, allowing k values from 0 to 1 and including both the minimum and maximum values in the calculation.

Syntax

PERCENTILEINC(array, k)

Arguments

The PERCENTILEINC function syntax has the following arguments:

  • array: The range or list of numeric values for which you want to calculate the percentile.

  • k: The percentile value to return, expressed as a decimal between 0 and 1.

    • 0 - Minimum value

    • 0.25 - 25th percentile

    • 0.5 - Median (50th percentile)

    • 0.75 - 75th percentile

    • 1 - Maximum value

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Example

PERCENTILEINC(10,20,30,40,50,60,70,80, 0.25)
// Returns 27.5
PERCENTILEINC(10,20,30,40,50,60,70,80, 0.5)
// Returns 45
PERCENTILEINC(10,20,30,40,50,60,70,80, 0.75)
// Returns 62.5

You can use the PERCENTILEINC function to determine the relative standing of values within a dataset by calculating specific percentiles for metrics such as sales, revenue, or performance scores.

PERCENTILEINC function
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We used the SELECT function to select a range of columns from 1 to 4 for the 'Revenue' measure (2022 Revenue - 2025 Revenue)

Excel Equivalent

PERCENTILEINCarrow-up-right

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PERCENTILE is the legacy version of the PERCENTILEINC function and works similarly. It can be used in place of PERCENTILEINC for inclusive percentile calculations.

FAQs

Q1. How is PERCENTILEINC calculated?

PERCENTILEINC is calculated by determining the k-th percentile of a dataset using the inclusive method, which includes the minimum and maximum values in the calculation.

Where:

  • k = desired percentile (between 0 and 1)

  • n = number of values

The result is interpolated if the position is not a whole number. It returns the value below which a specified percentage of data falls, including both the minimum and maximum values.

Q2. What does a percentile represent?

A percentile shows how a value compares to other values in a dataset.

For example, consider student exam scores. If a student’s score is at the 90th percentile:

  • 90% of the students scored below this value.

  • 10% of the students scored above this value.

This means the student performed better than most of the class and is among the top 10%.

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