PERCENTILE.EXC Function (LibreOffice Calc)

Math Intermediate LibreOffice Calc Introduced in LibreOffice 3.0
statistics data-analysis distribution percentiles exclusive-percentiles

The PERCENTILE.EXC function in LibreOffice Calc returns the k-th percentile of a dataset using the exclusive method. This guide explains syntax, examples, edge cases, errors, and best practices.

Compatibility

What the PERCENTILE.EXC Function Does

  • Returns the k‑th percentile of a dataset
  • Uses the exclusive method (k must be between 0 and 1, not including endpoints)
  • Works with numbers, ranges, and arrays
  • Useful for statistical modeling and academic analysis
  • Supports interpolation between values
  • Works across sheets

PERCENTILE.EXC is more mathematically strict than PERCENTILE.INC.

Syntax

PERCENTILE.EXC(range; k)
k must be greater than 0 and less than 1.
Example: 0.25 = 25th percentile.

Basic Examples

90th percentile (exclusive)

=PERCENTILE.EXC(A1:A100; 0.9)

25th percentile (exclusive)

=PERCENTILE.EXC(A1:A100; 0.25)

Median using PERCENTILE.EXC

=PERCENTILE.EXC(A1:A100; 0.5)

Invalid endpoints

=PERCENTILE.EXC(A1:A100; 0)   → error  
=PERCENTILE.EXC(A1:A100; 1)   → error

Advanced Examples

Percentile across sheets

=PERCENTILE.EXC((Sheet1.A1:A100; Sheet2.A1:A100); 0.9)

Percentile ignoring errors (using AGGREGATE)

=AGGREGATE(18; 2; A1:A100; 0.9)

Percentile of visible cells only (filtered data)

=AGGREGATE(18; 1; A1:A100; 0.9)

Conditional percentile (indirect)

=PERCENTILE.EXC(IF(B1:B100="North"; A1:A100); 0.9)

(Confirm with Ctrl+Shift+Enter in older Calc versions.)

Percentile excluding zeros

=PERCENTILE.EXC(IF(A1:A100<>0; A1:A100); 0.9)

Percentile using sorted helper column

=INDEX(SORT(A1:A100); ROUNDUP((COUNT(A1:A100)+1)*0.9; 0))

Percentile for statistical modeling

=PERCENTILE.EXC(Data; 0.95)

How PERCENTILE.EXC Calculates Values

  1. Sorts the dataset
  2. Computes position:
    position = (n + 1) * k
  3. Interpolates if position is not an integer
  4. Fails if position < 1 or > n

Example:
Dataset size = 10
k = 0.9
Position = (10 + 1) * 0.9 = 9.9
Result = 90% between 9th and 10th values.

Differences Between PERCENTILE.INC and PERCENTILE.EXC

Feature PERCENTILE.INC PERCENTILE.EXC
Allows k = 0 Yes No
Allows k = 1 Yes No
Formula basis (n‑1)*k + 1 (n+1)*k
Statistical strictness Standard Academic/strict
Use cases Grading, finance Research, modeling

Common Errors and Fixes

Err:502 — Invalid argument

Occurs when:

  • k ≤ 0 or k ≥ 1
  • Range contains no numeric values
  • Non-numeric text is included

Err:504 — Parameter error

Occurs when:

  • Semicolons are incorrect
  • Range is malformed

Percentile returns unexpected result

Possible causes:

  • Dataset contains zeros
  • Dataset contains errors
  • Hidden rows included

Fix:
Use AGGREGATE for visibility‑aware percentiles.

Percentile differs from PERCENTILE.INC

This is expected—EXC excludes endpoints and uses a different formula.

Best Practices

  • Use PERCENTILE.EXC for strict statistical analysis
  • Use PERCENTILE.INC for general-purpose percentile calculations
  • Use AGGREGATE for error‑tolerant or visibility‑aware percentiles
  • Use array formulas for conditional percentiles
  • Clean imported data before analysis
  • Use named ranges for cleaner formulas
PERCENTILE.EXC is ideal for academic statistics, research, and modeling where endpoints must be excluded.

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