QUARTILE.EXC Function (LibreOffice Calc)

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

The QUARTILE.EXC function in LibreOffice Calc returns a specified quartile of a dataset using the exclusive method. This guide explains syntax, examples, quartile logic, errors, and best practices.

Compatibility

What the QUARTILE.EXC Function Does

  • Returns quartiles using the exclusive percentile method
  • Allows quart values 1–3 only
  • Excludes minimum and maximum values
  • Useful for academic statistics and strict distribution analysis
  • Supports interpolation
  • Works across sheets

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

Syntax

QUARTILE.EXC(range; quart)

Where quart is:

Quart Meaning
1 25th percentile (Q1)
2 50th percentile (Median)
3 75th percentile (Q3)
QUARTILE.EXC is equivalent to:
PERCENTILE.EXC(range; quart/4)

Basic Examples

First quartile (Q1)

=QUARTILE.EXC(A1:A100; 1)

Median (Q2)

=QUARTILE.EXC(A1:A100; 2)

Third quartile (Q3)

=QUARTILE.EXC(A1:A100; 3)

Invalid quart values

=QUARTILE.EXC(A1:A100; 0)   → error  
=QUARTILE.EXC(A1:A100; 4)   → error

Advanced Examples

Quartile across sheets

=QUARTILE.EXC((Sheet1.A1:A100; Sheet2.A1:A100); 3)

Quartile ignoring errors (using AGGREGATE)

=AGGREGATE(19; 2; A1:A100; 3)

Quartile of visible cells only (filtered data)

=AGGREGATE(19; 1; A1:A100; 3)

Conditional quartile (indirect)

=QUARTILE.EXC(IF(B1:B100="North"; A1:A100); 1)

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

Quartile excluding zeros

=QUARTILE.EXC(IF(A1:A100<>0; A1:A100); 3)

Quartile using sorted helper column

=INDEX(SORT(A1:A100); ROUNDUP((COUNT(A1:A100)+1)*0.75; 0))

Quartile for strict statistical modeling

=QUARTILE.EXC(Data; 1)   → Q1  
=QUARTILE.EXC(Data; 2)   → Median  
=QUARTILE.EXC(Data; 3)   → Q3

How QUARTILE.EXC Calculates Values

QUARTILE.EXC uses the exclusive percentile formula:

position = (n + 1) * (quart / 4)

If position is not an integer, interpolation is used.

Example:
Dataset size = 10
Q1 = 0.25
Position = (10 + 1) * 0.25 = 2.75
Result = 75% between 2nd and 3rd values.

Differences Between QUARTILE.INC and QUARTILE.EXC

Feature QUARTILE.INC QUARTILE.EXC
Quart range 0–4 1–3 only
Includes min/max Yes No
Percentile basis Inclusive Exclusive
Use cases General statistics Academic/strict statistics

Common Errors and Fixes

Err:502 — Invalid argument

Occurs when:

  • quart is outside 1–3
  • Range contains no numeric values
  • Non-numeric text is included

Err:504 — Parameter error

Occurs when:

  • Semicolons are incorrect
  • Range is malformed

Quartile returns unexpected result

Possible causes:

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

Fix:
Use AGGREGATE for visibility‑aware quartiles.

Quartile differs from QUARTILE.INC

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

Best Practices

  • Use QUARTILE.EXC for strict statistical analysis
  • Use QUARTILE.INC for general-purpose quartile calculations
  • Use AGGREGATE for error‑tolerant or visibility‑aware quartiles
  • Use array formulas for conditional quartiles
  • Clean imported data before analysis
  • Use named ranges for cleaner formulas
QUARTILE.EXC is ideal for academic research, statistical modeling, and any analysis requiring strict exclusion of endpoints.

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