LOGNORM.DIST in Collabora Office: Use Natural-Log Parameters Correctly
Understand Collabora LOGNORM.DIST, distinguish log-scale parameters from raw-data averages, and calculate cumulative bands and densities.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
Quick answer: =LOGNORM.DIST(2;LN(2);LN(2);1) has independently expected result 0.5. In this example, two is the median on the original scale; the second and third arguments describe the natural-log scale.
Syntax and the two scales
=LOGNORM.DIST(Number; Mean; StDev; Cumulative)
All four arguments are required in the dedicated Collabora help. Number is the positive evaluation point. Mean and StDev parameterize the normal distribution of the natural logarithm of the modeled variable. StDev must be positive for the ordinary continuous model. Cumulative=0 selects density and Cumulative=1 selects cumulative probability.
The help’s wording “probability value” for Number should not be read as restricting it to the interval zero to one: this distribution evaluates a positive quantity such as a duration. The mean of that original quantity is not generally the Mean argument. Keep the natural-log and original scales explicitly labeled.
The independent definition is that LN(X) is normally distributed with mean mu and standard deviation sigma. Thus the cumulative probability at x is the standard-normal cumulative probability at (LN(x)-mu)/sigma.
Example 1: construct a log-spaced table
Put 1, 2, 4, 8 in A2:A5. Put =LN(2) in F2 for mu and again in F3 for sigma. Enter =LOGNORM.DIST(A2;$F$2;$F$3;1) in B2 and fill down.
Independent expected cumulative results are approximately 0.158655254, 0.5, 0.841344746, 0.977249868. Doubling x adds one sigma on the natural-log scale in this particular parameterization.
In C2 use =(LN(A2)-$F$2)/$F$3 and fill down. The expected standardized log values are −1, 0, 1, 2. This column explains the cumulative results and exposes an accidental use of base-ten logarithms.
The official example =LOGNORM.DIST(0.1;0;1;1) has independently expected value approximately 0.010651099. Its small evaluation point is allowed because it is positive; it does not mean Number must always be a probability.
Example 2: calculate an interval and a tail
For the same mu and sigma, the probability between one and four is =LOGNORM.DIST(4;$F$2;$F$3;1)-LOGNORM.DIST(1;$F$2;$F$3;1), independently approximately 0.682689492.
The probability beyond eight is =1-LOGNORM.DIST(8;$F$2;$F$3;1), independently approximately 0.022750132. These are modeled probabilities, not fractions automatically estimated from observed rows.
To compare density at two, use =LOGNORM.DIST(2;$F$2;$F$3;0), independently approximately 0.287776025 per original unit. A density is a curve height; it is not the probability of exactly two in a continuous model.
Advanced application: translate parameters back to the original scale
The median is EXP(mu). The original-scale arithmetic mean is EXP(mu+sigma^2/2). Here those values are 2 and approximately 2.543074259, respectively.
With F2 and F3 as above, use =EXP(F2) and =EXP(F2+F3^2/2) in separately labeled cells. The difference is expected for a right-skewed distribution. Entering the original-scale arithmetic average as mu would change the model.
If you are estimating parameters from positive observations, first create an LN-transformed column and use an explicitly chosen estimation procedure on that scale. This guide does not prescribe a fitting method or certify that your observations follow a lognormal distribution.
Errors and troubleshooting
Use positive observations and a positive log-scale standard deviation. Zero and negative original-scale data cannot be logged in this real-valued model. The dedicated function section does not document every native boundary, coercion or error display; such behavior remains unverified.
Check the logarithm base, the unit of Number and whether Mean was incorrectly copied from raw measurements. A change of physical units changes mu but not sigma when handled consistently. Keep full parameter precision for inverse checks; rounding logarithms early can shift quantiles noticeably.
Availability and verification
The exact function is documented in Collabora Office 26.04 desktop help. Its source snapshot was retrieved on 2026-10-13 and hash-verified for this guide on October 15, 2026. Desktop documentation is not proof of Online or mobile support.
First introduced release and last functioning version are unknown. The available dedicated source does not establish those releases. No native Collabora or WPS run occurred. Numerical values are independent mathematical expectations, not certification of application-specific errors, numerical tolerances or all edge cases. Formulas use English names and semicolon separators.
The help identifies the namespace COM.MICROSOFT.LOGNORM.DIST and says this function is outside the cited OpenFormula 1.3 standard. This format disclosure does not prove identical behavior in another product. Keep exact dotted names when checking imported workbooks.