AVEDEV in Collabora Office: Mean Absolute Deviation with a Centered Audit
Calculate Collabora AVEDEV from explicit distances to the mean, then compare a median-centered measure and changed measurement units.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
Quick answer: AVEDEV averages the absolute distances between numeric data points and their arithmetic mean. It measures spread in the original units. It does not calculate standard deviation or median absolute deviation.
Availability and version history
- Introduced: original Collabora release and launch date are not established by the reviewed sources.
- Availability: currently documented in Collabora Office 26.04 desktop help.
- Platform scope: online and mobile deployments are not inferred from this desktop-help release.
- Checked: October 14, 2026. Function-specific documentation and independent calculations; no native Collabora execution.
Syntax and included observations
=AVEDEV(argument1;[argument2];...)
Collabora permits up to 255 arguments, including ranges, and explicitly ignores text and empty cells inside a data range. A range can contain many observations while occupying one argument. These examples use English function names and semicolon separators.
The numeric model first finds the mean, measures each absolute distance from that mean, then averages the distances. Taking absolute values matters: the signed deviations from a mean sum to zero and would hide spread.
Example 1: reconstruct every distance
Enter 2, 4 and 10 in A2:A4:
=AVEDEV(A2:A4)
Expected result: 3.111111, displayed to six decimal places. The mean is 16/3, approximately 5.333333. Keep that full fraction for the calculation:
| Reading | Absolute distance from 16/3 |
|---|---|
| 2 | 10/3 |
| 4 | 4/3 |
| 10 | 14/3 |
Distances total 28/3. Dividing by three gives 28/9. A helper-column audit can put =AVERAGE(A2:A4) in C1 and =ABS(A2-$C$1) in B2, filled through B4. Averaging B2:B4 gives the same expected result.
Example 2: a label is different from a zero
Add text Pending in A5 and leave A6 genuinely empty. Extending the formula to A2:A6 still gives expected 28/9, following the documented range-ignore rule.
Replace Pending with numeric 0. The four numeric observations now have mean 4, with absolute distances 2,0,6,4. Their total is 12, so expected AVEDEV becomes 3.
Adding a low value decreased this particular average deviation because both the center and denominator changed. Do not assume that a new extreme observation must increase every spread statistic.
Advanced example: three different absolute-deviation measures
Return to the original 2,4,10 data. Its median is 4. Absolute distances from that median are 2,0,6:
- Their average is 8/3, approximately 2.666667.
- Their median is 2.
- AVEDEV remains 28/9, approximately 3.111111, because it centers on the arithmetic mean.
All three calculations use absolute distances, but they answer different questions. Label the center and final aggregation explicitly. MEDIAN explains the separately defined middle-value operation.
Advanced check: translation and scaling
For 102,104,110, the mean increases by 100 while all distances stay unchanged. Expected AVEDEV remains 3.111111.
For -4,-8,-20, each original value has been multiplied by -2. The distances double, and expected AVEDEV is 56/9, approximately 6.222222. The negative scale reverses ordering but cannot make absolute deviations negative.
Duplicating every original observation also preserves 28/9: both the distance total and count double. This is an arithmetic check, not a reason to duplicate source records.
Boundaries and troubleshooting
The explicit range rule does not settle direct text arguments, Boolean cells, formula-empty strings, source errors or every singleton/no-data result. Those cases remain unverified here. Inspect actual cell values when a supposedly numeric record seems absent.
DEVSQ uses squared centered distances instead of absolute distances. Its output therefore has different units and cannot be substituted into this calculation without changing the measure.
References and verification
Complete function-specific documentation reviewed. Worked outputs are independent mathematical or explicitly documented rule controls, not application screenshots or native test results. Unresolved ordering, type and error boundaries retain their stated scope.