# 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.

### Sample Usage

`NORMDIST(2.4,1,4,FALSE)`

`NORMDIST(A2,A3,A4,TRUE)`

### Syntax

`NORMDIST(x, mean, standard_deviation, cumulative)`

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

• `mean` - The mean (mu) of the normal distribution function.

• `standard_deviation` - The standard deviation (sigma) of the normal distribution function.

• `cumulative` - Whether to use the normal cumulative distribution function rather than the distribution function.

`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.

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

`NORMINV`: Returns the value of the inverse normal 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.