# VARP

The **VARP** function returns the population variance of a dataset. It measures how widely values are spread from the mean when the data represents the entire population. The calculation uses **n** in the denominator.

### Syntax

```javascript
VARP(number1, [number2], ...)
```

### Arguments

The **VARP** function syntax has the following arguments:

* number1, number2, ... - The numeric values for which you want to calculate the population variance. Required.

### Example

<pre class="language-javascript"><code class="lang-javascript"><strong>VARP(10, 20, 30)
</strong>// Returns 66.67
<strong>VARP(10, 20, 30, 40, 50)
</strong>// Returns 200
</code></pre>

You can use the **VARP** function to analyze how widely values are spread from the mean by calculating the population variance for metrics such as sales, revenue, or performance scores.

<figure><img src="/files/Dutr1spYXtYjhtc0FAV3" alt=""><figcaption><p>VARP function</p></figcaption></figure>

{% hint style="info" %}
We can also use the [**SELECT**](/planning-sheets/formula-syntax/measure-column-selection-functions/select.md) function to select a range of columns from 1 to 4 for the 'Revenue' measure (2022 Revenue - 2025 Revenue)

<pre><code><strong>VARP(SELECT([Revenue], 1, 4))
</strong></code></pre>

{% endhint %}

### Excel Equivalent

[VARP](https://support.microsoft.com/en-us/office/varp-function-26a541c4-ecee-464d-a731-bd4c575b1a6b)

{% hint style="info" %}
[**VARS** ](/planning-sheets/formula-syntax/statistical-functions/vars.md)calculates the sample variance using (n − 1) in the denominator and should be used when working with a sample dataset, whereas **VARP** calculates the population variance using (n) in the denominator and should be used when working with the entire population.
{% endhint %}

### FAQs

**Q1. How is VARP calculated?**

VARP (Population Variance) is calculated by taking the sum of squared deviations from the mean and dividing it by n.

<figure><img src="/files/HnPiEcL4xftIGJK7D7YX" alt="" width="195"><figcaption></figcaption></figure>

Where:

* x = each value in the dataset
* <img src="/files/7kgTtFg5mZ5tcXpS74Op" alt="" data-size="line"> = mean of the values
* n = number of values

It measures how widely the values are spread from the mean by calculating the population variance, which represents the average squared deviation from the mean when the data represents the entire population.


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