# GAUSS

The GAUSS function in Excel is used to return the normal distribution of a specified value.

## Syntax ðŸ”—

=GAUSS(`Z`

)

`Z` | The value at which to evaluate the standard normal distribution. |

## About GAUSS ðŸ”—

When you need to determine the probability of a value occurring within a standard normal distribution, the GAUSS function in Excel comes to your aid. It allows you to quickly calculate the probability of a specified value occurring in a standard normal distribution curve, providing valuable insights for statistical analysis and decision-making processes. Whether you're delving into risk assessment, quality control, or hypothesis testing, the GAUSS function offers a straightforward solution for assessing probabilities within a standard normal distribution.

## Examples ðŸ”—

Suppose you want to find the probability of a value occurring within a standard normal distribution with a Z-score of 1.5. The formula using GAUSS would be: =GAUSS(1.5)

If you need to calculate the probability of a Z-score of -0.75 occurring within a standard normal distribution, you would use: =GAUSS(-0.75)

## Notes ðŸ”—

The GAUSS function calculates the cumulative distribution function for a standard normal distribution. The value supplied to the function should correspond to a Z-score in a standard normal distribution curve.

## Questions ðŸ”—

**What does the GAUSS function output represent?**

The output of the GAUSS function signifies the cumulative probability of a specified value occurring in a standard normal distribution.

**Can the GAUSS function be used for non-standard normal distributions?**

No, the GAUSS function is specifically designed for standard normal distributions where the mean is 0 and the standard deviation is 1. For non-standard normal distributions, you may need to apply additional transformations or consider other statistical functions.

**How precise are the results provided by the GAUSS function?**

The results offered by the GAUSS function are based on the standard normal distribution assumptions and provide accurate estimations of probabilities within this particular context. Ensure that the Z-value provided corresponds to the standard normal distribution for reliable results.