Syntax
LOGNORM.INV(probability, mean, standard_dev)
| Parameter | Description |
|---|---|
| probability | Parameter of the LOGNORM.INV function. |
| mean | Parameter of the LOGNORM.INV function. |
| standard_dev | Parameter of the LOGNORM.INV function. |
Examples
Value at Risk (95th percentile)
Formula
=LOGNORM.INV(0.95, LN(1000000), 0.3)
Returns ~1,636,462. There is a 95% probability that the portfolio value stays below ~$1.64M under lognormal assumptions.
Median project cost
Formula
=LOGNORM.INV(0.5, 11.5, 0.6)
Returns ~98,716. The median estimated project cost is about $99K. This equals EXP(11.5).
Lower 10% failure threshold
Formula
=LOGNORM.INV(0.10, 8, 0.5)
Returns ~1,565. 10% of components fail before reaching 1,565 cycles.
Common Errors
#NUM!
Probability must be strictly between 0 and 1, and standard_dev must be greater than 0.
#VALUE!
Returned when any argument is non-numeric.
Tips
Parameters are for ln(x)
The mean and standard_dev describe the underlying normal distribution of ln(x). If you know the geometric mean of your data, pass LN(geometric_mean) as the mean.
Build prediction intervals
Use LOGNORM.INV(0.025, m, s) and LOGNORM.INV(0.975, m, s) to create a 95% prediction interval for lognormally distributed outcomes.
Always returns positive values
Because the lognormal distribution only produces positive values, LOGNORM.INV always returns a number greater than 0, regardless of the probability input.
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