LOGNORM.DIST in ONLYOFFICE: Lognormal CDF and Density with Log-Scale Inputs

Create DurationModel. Put Parameter in A1 and Value in B1, then enter these values and one formula:

This is an assumed lognormal model for a fictional task duration, not observed data. If X is the duration measured numerically in minutes, ln(X) is modeled as normal with mean μ and standard deviation σ. Use natural logarithms, not base-10 logarithms. The numerical unit must stay consistent when transforming data.

Here exp(μ)=10 is the median, not the arithmetic mean duration. The arithmetic mean is exp(μ+σ²/2), approximately 11.3314845306683 minutes; the mode is exp(μ−σ²), approximately 7.78800783071405. Entering 10 as the mean argument instead of LN(10) specifies a radically different model. A positive skew does not by itself prove real data follow a lognormal distribution.

The official reference has four required arguments. TRUE returns a left-tail cumulative probability, P(X≤x). FALSE returns a continuous density. A density is a height per unit of duration; it is not the probability of finishing at one exact minute. For a continuous model, the probability at an exact point is zero.

For positive x, standardize the logarithm as z=(ln(x)−μ)/σ. The CDF is Φ(z), while the density is φ(z)/(σx). The extra division by x is essential; simply using a normal density for ln(x) does not give the density of X.

D5 is the modeled share between 5 and 20 minutes. Those endpoints are equally spaced around LN(10) on the log scale, not around 10 on the original scale. D7 and D8 are densities; do not format them as a percentage of tasks taking exactly 10 or 20 minutes.

In F2 put =(LN(B6)-B2)/B3, with target about 1.38629436111989. =NORM.S.DIST(F2,TRUE) has the same mathematical CDF target as D4. For density, =NORM.S.DIST(F2,FALSE)/(B3*B6) reconstructs D8. These are mathematical checks, not evidence of identical rounding in a running editor.

A time-unit conversion changes the logarithmic mean. If minutes are multiplied by 60 to obtain seconds, add LN(60) to μ and keep σ unchanged. Merely multiplying μ by 60 would be wrong. Percentiles scale with the original duration units, whereas the spread of logarithms does not change under this constant multiplication.

Help restricts x to positive values. The pinned code is more permissive in the cumulative branch: with σ>0, x≤0 returns 0. Thus =LOGNORM.DIST(0,LN(10),0.5,TRUE) is source-predicted 0, while the same call with FALSE is source-predicted #NUM!. A nonpositive σ is rejected in both modes. These boundary observations are version-pinned source facts, not native measurements.

LOGNORMDIST is a three-argument cumulative-only function and rejects x≤0. Do not treat the two interfaces as interchangeable punctuation variants. The modern path also uses array-oriented preparation, whereas the legacy path selects the first element of explicit arrays; no spill workflow is established here.

The CDF uses 0.5+gauss on the standardized log value. The source’s normal-helper comment warns of cancellation in sufficiently negative tails. Avoid inferring high relative accuracy for extremely small probabilities from the moderate examples above. Errors in argument conversion propagate; use explicit TRUE or FALSE rather than undocumented numeric coercion of the mode.

Checked October 18, 2026 against current official help and SDKJS tag v10.0.0.169, commit 3679e0375a758d7dc59d31337a45461be3525ed8. Introduction dates and a final supported-version endpoint are not established. Desktop Editors, Docs, mobile releases and imported files require separate compatibility checks.

Neither the ONLYOFFICE application nor its calculation engine was executed for this guide. The numerical targets are independently calculated mathematical values; code-path and error observations are manual source traces. They are not screenshots, displayed workbook results or promises of identical final digits. Use English function names and comma separators as shown, adapting separators to the editor’s locale.

Keep inputs and intermediate probabilities numeric and unrounded. Format the display rather than replacing values with rounded strings. These moderate scalar examples do not certify extreme-tail accuracy, unusual type coercion, array entry or dynamic spill. Model assumptions must be checked separately from arithmetic correctness.

• Official LOGNORM.DIST reference, checked October 18, 2026.
• Pinned implementation.
• Pinned normal helpers and beta helper.
• LOGNORMDIST.
• LOGNORM.INV.
• LOGINV.
• NORM.S.INV and NORM.S.DIST.