# LOGNORM.INV

Formulas / LOGNORM.INV
Calculate the inverse of the lognormal cumulative distribution function.
`LOGNORM.INV(probability, mean, std_dev)`
• probability - required, value at which the inverse function is to be evaluated
• mean - required, average of ln(x)
• standard_dev - required

## Examples

The function can be used to calculate the inverse lognormal cumulative distribution. For example, if we have three inputs of A2=0.4, A3=2, and A4=1, the function would return a value of 0.8147.

The function can also be used to calculate the inverse of the lognormal cumulative probability. For example, if we have three inputs of A2=0.85, A3=1.5, and A4=0.5, the function would return a value of 2.2449.

The function can also be used to calculate the inverse of the lognormal cumulative distribution for a given set of parameters. For example, if we have three inputs of A2=0.2, A3=4, and A4=2, the function would return a value of 6.6349.

The function can also be used to calculate the inverse of the lognormal cumulative probability for a given set of parameters. For example, if we have three inputs of A2=0.95, A3=3, and A4=1.5, the function would return a value of 4.6845.

## Summary

The LOGNORM.INV function is used to calculate the inverse of the lognormal cumulative distribution function, which is used to analyze logarithmically transformed data.

• The LOGNORM.INV function is used to find the inverse of the lognormal cumulative distribution function.
• The lognormal distribution is used to analyze data that has been logarithmically transformed.

What is the LOGNORM.INV function?
The LOGNORM.INV function calculates the inverse of the lognormal cumulative distribution function.
What is the lognormal distribution?
The lognormal distribution is used to analyze logarithmically transformed data.
What is the syntax for the LOGNORM.INV function?
The syntax for the LOGNORM.INV function is LOGNORM.INV(probability, mean, standard_dev).
What are the arguments of the LOGNORM.INV function?
The arguments of the LOGNORM.INV function are probability, mean, and standard_dev.
Is the probability argument required?
Yes, the probability argument is required.
What is the probability argument?
The probability argument is a probability associated with the lognormal distribution.
Is the mean argument required?
Yes, the mean argument is required.
What is the mean argument?
The mean argument is the mean of ln(x).
Is the standard_dev argument required?
Yes, the standard_dev argument is required.