VAR.S Function
VAR.S Function

VAR.S Function

Measure variance for a sample. Use it when your data is only part of a larger population.

ExcelClash Team
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Summary

VAR.S returns the variance for a sample. Variance measures spread too, but it does so in squared units, which is why many people find standard deviation easier to read. Even so, variance is still important because it is part of the math behind standard deviation and many statistical models.

The .S means sample. Use this version when the values you have are only part of a larger population.

VAR.S plays the same role for sample data rather than full-population data. It helps the workbook estimate spread under a sampling assumption, which is why it is commonly paired with STDEV.S in statistical analysis tasks.

Purpose

Measure sample variance

Shows how spread out a sample is around its mean, in squared units.

Return Value

Positive Number

Returns the sample variance. Larger values mean more spread.

Syntax

=VAR.S(number1, [number2], ...)

You can use a range, separate references, typed values, or a mix.

Arguments

  • number1 - [required] The first number, range, or reference in the sample.
  • number2, ... - [optional] Additional sample values or ranges.

VAR.S vs Other Functions

Function What it measures Use it when
VAR.S Sample variance You have a sample, not the full population
VAR.P Population variance You have the full population
STDEV.S Sample standard deviation You want the sample spread in the original units
AVERAGE Center point You want the mean, not the spread

Using the VAR.S Function

Variance and standard deviation talk about the same idea, which is spread, but they express it differently. Variance uses squared units, so the number is not as intuitive to read directly. That is why people often report standard deviation, while variance stays useful for calculation and deeper analysis.

Microsoft notes that VAR.S assumes the data is a sample from a population. It also notes that logical values and text representations of numbers typed directly into the argument list are counted, while text and logical values inside references are ignored. Blank cells in references are ignored too.

When you compare two samples, the one with the larger VAR.S result has more spread around its mean. The one with the smaller result is more tightly clustered.

Example 1 - Measure sample variance in a range

This is the standard pattern when the sample is already stored in cells.

=VAR.S(B1:B5) // Returns the sample variance for the range.
Check Answer
Challenge #1
Target: Sheet1!C1

Find the sample variance of the first range.

Example 2 - Check a tight sample

Values that stay close together produce a smaller variance.

=VAR.S(10,11,10) // Returns a relatively small sample variance.
Check Answer
Challenge #2
Target: Sheet1!C2

Find the sample variance of the tight typed set.

Example 3 - Check a wide sample

A wider gap between sample values pushes the variance up quickly.

=VAR.S(10,90) // Returns a much larger sample variance.
Check Answer
Challenge #3
Target: Sheet1!C3

Find the sample variance of the wide typed set.

Example 4 - Use it as a sample spread check

This helps when you want a sample-based spread measure, especially for deeper statistical work.

=VAR.S(B1:B10) // Returns the sample variance for the range.
Check Answer
Challenge #4
Target: Sheet1!C4

Find the sample variance of the full sample range.

Conclusion Recap

VAR.S is the sample version of variance, so it is the one to use when your data is only part of a larger population. This lesson showed that it measures spread like standard deviation does, but in squared units instead of the original scale.

That makes VAR.S useful for analysis, even if it feels less natural to read at first. A bigger result still means the sample is more spread out, and a smaller result means it is tighter. If you want the sample spread in the original units, STDEV.S is the easier companion function.

  • Main job: VAR.S measures sample variance.
  • Use it for samples: Choose it when the data is only part of a larger population.
  • Variance is squared spread: It describes the same idea as standard deviation, but in squared units.
  • Larger result means more spread: Smaller result means tighter clustering.
  • Reference behavior: Text and logical values in references are ignored.
  • Related option: Use STDEV.S if you want the spread in the original units.
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