POISSON.DIST in Collabora Office: Calculate Count Probabilities for a Fixed Interval
Use Collabora POISSON.DIST to separate exact counts and cumulative counts, scale the expected count to its interval, and audit upper tails.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
Quick answer: =POISSON.DIST(2;3;0) has independently expected result approximately 0.224041808. It is the probability of exactly two events in an interval whose Poisson-model mean count is three.
Syntax and event-count model
=POISSON.DIST(Number; Mean; Cumulative)
Number is the count being evaluated. Mean is the expected count for the same observation interval. Cumulative zero or FALSE selects the probability mass; the dedicated help says one, TRUE or any other nonzero value selects the cumulative distribution. Supply an explicit zero or one.
Use whole-number nonnegative counts and a positive Mean in the ordinary examples here. The Poisson model describes event counts under appropriate rate and independence assumptions. It is not automatically suitable for clustered, dependent or capacity-limited events.
Mean is a count for an interval, not a rate with unspecified units. If the rate is three events per hour and the question concerns two hours under a constant-rate model, the mean count is six.
Example 1: verify an exact count
Put 2, 3, 0 in B2:B4, labeled Count, Mean count and Cumulative flag. Use =POISSON.DIST(B2;B3;B4) in B6.
The independent Poisson mass formula is EXP(-3)*3^2/FACT(2), giving approximately 0.224041808. This is an exact-count probability mass, not a continuous curve density.
For zero events with the same mean, the independent target is EXP(−3), approximately 0.049787068. That provides a simple additional control without a factorial beyond 0!=1.
Example 2: calculate at most two
=POISSON.DIST(2;3;1) has independent target approximately 0.423190081. It adds probabilities for counts zero, one and two.
For an auditable table, put 0, 1, 2 in A10:A12, use =POISSON.DIST(A10;3;0) in B10, and fill down. Summing B10:B12 should target the same cumulative value.
The distribution has no finite maximum count. A short table ending at two does not sum to one; its total is the probability that the count lies in that displayed subset.
Advanced application: form complementary events
“At least one event” is the complement of zero events. =1-POISSON.DIST(0;3;1) has independently expected result approximately 0.950212932.
“More than two events” is =1-POISSON.DIST(2;3;1), independently approximately 0.576809919. “At least two” instead subtracts the cumulative probability through one. Those phrases differ because two itself has nonzero probability.
Write the event in words beside the formula. This simple practice helps prevent an off-by-one change when someone edits a threshold.
Advanced application: scale the observation window
With a constant expected rate of three events per hour, a two-hour interval has Mean=6. Its zero-event probability is =POISSON.DIST(0;6;0), independently approximately 0.002478752.
This equals EXP(−6), and also equals the square of EXP(−3) when the two hourly intervals are modeled independently. The agreement checks the rate-to-count conversion under those assumptions.
A changing rate, dependence between intervals or event clustering invalidates that simple extrapolation. The function receives the mean you provide; it does not investigate those process characteristics.
Errors and troubleshooting
Validate a whole nonnegative count and a numeric mean matched to the interval. The dedicated section does not document all fractional-count coercion, zero-mean boundaries or native invalid-input codes; those cases remain unverified here.
If a result looks too small, check whether a rate per minute was paired with an interval in hours without conversion. If a table total looks incomplete, remember the Poisson distribution has an unbounded count range. Extreme-tail numerical accuracy should be tested in the actual application.
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. No native Collabora or WPS run occurred. The numerical values are independent mathematical expectations; they do not certify application-specific numerical tolerances, error codes or every edge case. Formulas use English names and semicolon separators.
The dedicated help identifies the namespace COM.MICROSOFT.POISSON.DIST and says this function is outside the cited OpenFormula 1.3 standard. That is a format-namespace disclosure, not evidence of identical behavior in another product. Retain the exact dotted name when checking an imported workbook.