LOGNORMDIST
Definition of LOGNORMDIST
Returns the value of the lognormal cumulative distribution with given mean and standard deviation at a specified value.
Sample Usage
LOGNORMDIST(4,4,6)
LOGNORMDIST(A2,A3,A4)
Syntax
LOGNORMDIST(x, mean, standard_deviation)
x
 The input to the lognormal cumulative distribution function.mean
 The mean (mu) of the lognormal cumulative distribution function.standard_deviation
 The standard deviation (sigma) of the lognormal cumulative distribution function.
Notes
 A lognormal distribution function is a probability distribution function of a random variable whose logarithm is normally distributed.
See Also
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.
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.
NORMDIST
: 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.
LOGINV
: Returns the value of the inverse lognormal cumulative distribution with given mean and standard deviation 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.
To use the LOGNORMDIST Formula, simply begin with your edited Excellentable:
Then begin typing the LOGNORMDIST formula in the area you would like to display the outcome:
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