VARPA in Collabora Office: Population Variance with Text and Explicit Inclusion Counts

• 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.

=VARPA(argument1;[argument2];...)

The Collabora reference permits up to 255 arguments, including numbers, text and cell references. The documented text value is zero. This guide uses ordinary words to make that rule explicit and avoids assuming numeric-text, logical or error conversions.

Before using this population measure, define why a text category should participate numerically. Preserve the original status and the actual measurement count so readers can distinguish encoded data from collected values.

Enter 2, 6 and Pending in A2:A4:

=VARPA(A2:A4)

Expected result: 6.222222, displayed to six decimal places. Encoded values are 2,6,0, with mean 8/3. Squared deviations are 4/9,100/9 and 64/9, totalling 56/3. Dividing by three gives variance 56/9.

The result is in squared units. Its square root, approximately 2.494438, would be a population standard deviation rather than variance.

For the numeric-only population 2,6, the mean is 4 and population variance is 4. Encoding Pending as zero gives the larger 56/9 result above.

The difference does not establish that either policy is appropriate for a real reporting question. If Pending means a reading has not arrived, keep that missingness visible rather than describing the encoded zero as a measured result.

Put text Review in A5. The four encoded values become 2,6,0,0, with mean 2. Squared deviations are 0,16,4,4, totalling 24.

=VARPA(A2:A5)

Expected result: 6. The variance decreases slightly from 56/9 despite an additional zero-valued text entry. Both the center and denominator changed.

A rule that “more missing values always increase spread” would fail on this explicit example. Review data completeness separately from the statistic.

Return to A2:A4 and replace Pending with numeric 4. Values 2,6,4 have mean 4 and squared-deviation total 8. Expected VARPA is 2.666667, from 8/3.

All three observations are now actual numbers. The variance is lower, but the important reporting change is also the replacement of an encoded status by a measurement.

For 2,6,Pending,2,6,Pending, the encoded mean stays 8/3. Squared deviations double to 112/3 and the count doubles to six. Population variance remains 56/9, approximately 6.222222.

This invariance is an independent arithmetic check, not permission to duplicate records. Counts, sums and the provenance of the population still change when rows are repeated.

For the original three encoded values, the sample-variance model would divide 56/3 by two, giving 28/3, approximately 9.333333. VARA uses that sample interpretation.

The dedicated text rule does not resolve genuinely empty cells, formula-empty results, Boolean values, numeric-looking strings, source errors or every one-value case. Those remain unverified rather than inferred from similarly named functions in another product.

STDEVPA describes the population standard-deviation interpretation with text encoding. Compare like units and inclusion policies, and retain full precision until the final displayed report.

• Collabora Office 26.04: VARPA.
• Editorial testing standards.

Complete function-specific documentation reviewed. Worked outputs are independent mathematical or explicitly documented type-rule controls, not application screenshots or native test results. The stated unresolved boundaries retain their scope.