VAR.P in Collabora Office: Population Variance and Squared-Unit Transformations

• 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.

=VAR.P(argument1;[argument2];...)

The dedicated Collabora section lists up to 255 arguments, including references and ranges. These controls use ordinary numbers and at least four observations. Text, logical, empty and error-valued cases are not inferred from the syntax’s broad argument description.

Population is a definition of the records under study, not a promise created by choosing a function ending in .P. State the period, cohort or complete batch that the input represents.

Enter 1, 3, 5 and 7 in A2:A5:

=VAR.P(A2:A5)

Expected result: 5. The mean is 4. Deviations -3,-1,1,3 produce squares 9,1,1,9, totalling 20. Dividing by four gives population variance 5.

For comparison, the population standard deviation is sqrt(5), approximately 2.236068. STDEV.P returns the corresponding original-unit measure.

=VAR.P(101;103;105;107)

Expected result: 5 again. Adding 100 raises the mean to 104, leaving all centered differences unchanged. Variance is not a measure of the level of the observations.

The two populations have very different means even though their variance agrees. Report both measures when the location as well as spread matters.

For 10,30,50,70, obtained by multiplying the original values by ten, expected population variance is 500. Squared deviations total 2000 and the denominator remains four.

The standard deviation increases tenfold, while variance increases one hundredfold. When comparing values expressed in different units, convert the source observations consistently or transform the variance by the square of the conversion factor.

Multiplying by -2 gives the population -2,-6,-10,-14 and expected variance 20. A negative scale factor still has a positive squared effect.

Split the original values into groups 1,3 and 5,7. Each group has population variance 1, with centers 2 and 6. The combined population variance is 5, not the simple average 1.

The combined calculation includes the separation between group centers. Keep counts and centers available, or calculate from the original observations, when combining reports.

Add numeric 4 to the original population. Its mean stays 4 and squared deviations still total 20, but the count becomes five. The independent expected variance is now 4.

An observation at the mean contributes no squared deviation but still contributes to the population denominator. It is not the same as leaving a row outside the calculation.

Collabora documents COM.MICROSOFT.VAR.P and identifies it as outside the cited OpenFormula 1.3 standard. The namespace is not a native compatibility test or an introduction date.

The reference does not provide a full singleton, empty-range or mixed-type error matrix. These examples establish numerical population calculations within a clear scope. VAR.S uses a different sample denominator; switching between them requires an explicit statistical reason.

• Collabora Office 26.04: VAR.P.
• 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.