> For the complete documentation index, see [llms.txt](https://docs.inforiver.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.inforiver.com/formula-syntax/statistical-functions/normsinv.md).

# NORMSINV

Calculates the inverse of the standard normal cumulative distribution to find the z-score for a given probability with a mean of 0 and a standard deviation of 1.

The **NORMSINV** function returns the inverse of the standard normal cumulative distribution. It assumes a distribution with a mean of 0 and a standard deviation of 1. 

### Syntax

<pre class="language-javascript"><code class="lang-javascript"><strong>NORMSINV(probability)
</strong></code></pre>

### Arguments

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

* probability - A probability corresponding to the normal distribution. Required.

### Example

<pre class="language-javascript"><code class="lang-javascript"><strong>NORMSINV(0.90)
</strong>// Returns 1.28
</code></pre>

You can use the **NORMSINV** function to determine the number of standard deviations a value is from the mean. This is particularly useful for creating standardized benchmarks or z-scores across different datasets to compare them on a level playing field.

<figure><img src="https://3062809325-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FEbkCXCUXmtUq5tcnUtZE%2Fuploads%2FpIGb71za2iBf8CJPbMnJ%2F2026-02-18_13h45_40.png?alt=media&amp;token=51d578da-ea56-485a-b19b-ea46e31ad9b1" alt=""><figcaption><p>NORMSINV function</p></figcaption></figure>

### Excel Equivalent

[NORMSINV](https://support.microsoft.com/en-us/office/normsinv-function-8d1bce66-8e4d-4f3b-967c-30eed61f019d)

### FAQs

**Q1. What is the difference between NORMINV and NORMSINV?**

* [NORMINV](/formula-syntax/statistical-functions/norminv.md) allows you to specify any mean and standard deviation for your dataset.&#x20;
* NORMSINV is a specialized version that always uses a mean of 0 and a standard deviation of 1.


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