## Excel LOGNORMDIST Function

The LOGNORMDIST function returns the cumulative lognormal distribution for a given value of x. We can use this function to analyze data that has been logarithmically transformed.

Note: The LOGNORMDIST function has been replaced with LOGNORM.DIST with improved accuracy. Although LOGNORMDIST is still available in current versions of Excel, you should consider using the new function from now on, because LOGNORMDIST may not be available in Excel’s future versions.

#### Syntax

=LOGNORMDIST(x, mean, standard_dev)

#### Arguments

• x (required): The value at which to evaluate the lognormal distribution.
• mean (required): The arithmetic value of the mean of ln(x).
• standard_dev (required): The value of the standard deviation of ln(x).</li

#### Return Value

The LOGNORMDIST function returns a numeric value.

#### Function Notes

• LOGNORMDIST returns the #VALUE! error value if any argument is non-numeric.
• LOGNORMDIST returns the #NUM! error value if:
• x ≤ 0.
• standard_dev ≤ 0.

#### Example

To calculate the cumulative lognormal distribution at 7 with the given mean, and standard deviation as shown in the table below, please copy or enter the below formula in the result cell (D6), and press Enter to get the result.

=LOGNORMDIST(B6,B9,B12)

Also, you can type the actual x, mean, and standard_dev values in the formula as shown below.

=LOGNORMDIST(7,2,1)

#### Related functions

Excel LOGNORM.DIST Function

The LOGNORM.DIST function calculates the lognormal distribution for a given value of x. We can use this function to analyze data that has been logarithmically transformed.

Excel WEIBULL.DIST Function

The Excel WEIBULL.DIST function returns the Weibull probability density function or Weibull cumulative distribution for a supplied set of parameters. It is frequently used for reliability analysis, e.g., for testing the mean time of the failure of an equipment in a specific time range.

Excel POISSON.DIST Function

The Excel POISSON.DIST function returns the Poisson distribution which is used to predict the number of events occurring over a specific time, e.g., the number of people arriving at the market in 10 minutes.

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