# NORMSDIST

Returns the value of the standard normal cumulative distribution function for a specified value.

### Sample Usage

`NORMSDIST(2.4)`

`NORMSDIST(A2)`

### Syntax

`NORMSDIST(x)`

• `x` - The input to the standard normal cumulative distribution function.

### Notes

• The "standard" normal distribution function is the normal distribution function with mean of `0` and variance (and therefore standard deviation) of `1`.

### See Also

`ZTEST`: Returns the one-tailed P-value of a Z-test with standard distribution.

`WEIBULL`: Returns the value of the Weibull distribution function (or Weibull cumulative distribution function) for a specified shape and scale.

`POISSON`: Returns the value of the Poisson distribution function (or Poisson cumulative distribution function) for a specified value and mean.

`NORMSINV`: Returns the value of the inverse standard normal distribution function for a specified value.

`NORMINV`: Returns the value of the inverse normal distribution function for a specified value, mean, and standard deviation.

`NORMDIST`: The NORMDIST function returns the value of the normal distribution function (or normal cumulative distribution function) for a specified value, mean, and standard deviation.

`NEGBINOMDIST`: Calculates the probability of drawing a certain number of failures before a certain number of successes given a probability of success in independent trials.

`LOGNORMDIST`: Returns the value of the log-normal cumulative distribution with given mean and standard deviation at a specified value.

`LOGINV`: Returns the value of the inverse log-normal cumulative distribution with given mean and standard deviation at a specified value.

`EXPONDIST`: Returns the value of the exponential distribution function with a specified lambda at a specified value.

`BINOMDIST`: Calculates the probability of drawing a certain number of successes (or a maximum number of successes) in a certain number of tries given a population of a certain size containing a certain number of successes, with replacement of draws.

### Examples

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