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.

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.

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.

Examples

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