NORMDIST in Calligra Sheets: Normal Density vs Cumulative Probability
Calculate normal-curve densities or cumulative probabilities in Calligra Sheets with four-argument NORMDIST, sample worksheets and source-checked limits.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
Quick answer: =NORMDIST(110;100;10;1) has expected result 0.841344746069, the fraction below 110 in a normal model with mean 100 and standard deviation 10. With the final argument changed to 0, the result is 0.024197072452, a density.
Availability and version history
- Introduced: First release not established. The name is registered in Calligra 2.4.0, which proves historical presence, not introduction.
- Availability: Supported in Calligra Sheets 26.08.2, according to the release-pinned registration.
- Scope: Desktop Sheets with the statistical functions module available. Names and separators can depend on locale.
- Checked: October 14, 2026. Official documentation/source and independent mathematical examples checked; Calligra was not run.
What NORMDIST does
NORMDIST evaluates either the cumulative distribution function (CDF) or probability density (PDF) of a normal distribution. For a continuous variable, density at a point is not the probability of observing that exact value. Probabilities are areas under the curve. KDE function handbook.
The mathematical relationship is z=(x−μ)/σ; density=exp(−z²/2)/(σ√(2π)); CDF=Φ(z). Φ denotes the standard-normal cumulative distribution. These formulas describe an assumed probability model; successful calculation does not establish that a normal distribution fits a real dataset.
Syntax and arguments
=NORMDIST(Number; MV; STD; K)
| Argument | Meaning |
|---|---|
| Number | The value x at which to evaluate the model. |
| MV | The mean μ, in the same units as x. |
| STD | Positive standard deviation σ, in the same units as x. |
| K | 0 selects density; 1 selects cumulative probability. |
All listed arguments are required; there is no documented default to substitute for an omitted input. Use semicolons as shown in the English KDE examples, decimal points in the sample data, and the separators accepted by your installation. Release-pinned function help.
Reproducible worksheet
Enter the numeric inputs into the stated columns, then enter the indicated result formula. Fill through row 12. The expected results are mathematical references rounded to twelve decimal places; a displayed probability used as a new input can differ slightly from its unrounded original.
| Row | X (A) | Mean (B) | SD (C) | Mode (D) | Formula in E | Independently expected output |
|---|---|---|---|---|---|---|
| 2 | 100 | 100 | 10 | 1 | =NORMDIST(A2;B2;C2;D2) |
0.5 |
| 3 | 110 | 100 | 10 | 1 | =NORMDIST(A3;B3;C3;D3) |
0.841344746069 |
| 4 | 90 | 100 | 10 | 1 | =NORMDIST(A4;B4;C4;D4) |
0.158655253931 |
| 5 | 120 | 100 | 10 | 1 | =NORMDIST(A5;B5;C5;D5) |
0.977249868052 |
| 6 | 80 | 100 | 10 | 1 | =NORMDIST(A6;B6;C6;D6) |
0.022750131948 |
| 7 | 100 | 100 | 10 | 0 | =NORMDIST(A7;B7;C7;D7) |
0.03989422804 |
| 8 | 110 | 100 | 10 | 0 | =NORMDIST(A8;B8;C8;D8) |
0.024197072452 |
| 9 | 0 | 0 | 1 | 1 | =NORMDIST(A9;B9;C9;D9) |
0.5 |
| 10 | 0 | 0 | 1 | 0 | =NORMDIST(A10;B10;C10;D10) |
0.398942280401 |
| 11 | 0.859 | 0.6 | 0.258 | 0 | =NORMDIST(A11;B11;C11;D11) |
0.934235884441 |
| 12 | 0.859 | 0.6 | 0.258 | 1 | =NORMDIST(A12;B12;C12;D12) |
0.842280799519 |
Worked applications
Probability between two thresholds
For a normal model with mean 100 and standard deviation 10, ask what fraction lies between 90 and 110:
=NORMDIST(110;100;10;1)-NORMDIST(90;100;10;1)
The expected probability is 0.682689492137, about 68.27%. Reversing the bounds changes the sign; always keep lower and upper limits in order. If x is measured in minutes, the CDF is unitless, whereas density has units of inverse minutes.
Convert a measurement to a z-score
For 110, mean 100 and SD 10, (110−100)/10=1. =NORMSDIST(1) gives the same expected cumulative probability, 0.841344746069. This checks the standardization, not whether a normal model fits your observations.
Errors and numerical limits
STD must be positive. The release returns an internal value-error object for zero or negative standard deviation. Its computation tests whether K is zero and uses the cumulative branch otherwise; use the documented 0/1 selector rather than relying on arbitrary nonzero values or text conversion. Release computation and guards.
For an ordinary upper-tail question, =1-NORMDIST(110;100;10;1) has expected probability 0.158655253931. Extremely small tails can lose precision when subtracting a value near 1. The source CDF also adds 0.5 to its centered-normal helper, so do not assume a symmetry rewrite guarantees extreme-tail accuracy.
An internal Value::errorVALUE() in the source identifies the error category, not a guarantee of the same visible token in every package or locale. Validate numeric input cells and units rather than depending on implicit text or blank-cell conversion.
Related functions and compatibility
NORMDIST supplies the general normal CDF or density; NORMINV reverses its CDF. NORMSDIST and NORMSINV use mean zero and standard deviation one. Follow each function’s own argument contract instead of adding or omitting a flag by analogy.
Other spreadsheet programs may use dotted names such as NORM.DIST or NORM.S.INV. A related mathematical name does not prove that an imported formula, error display or locale separator transfers unchanged. Validate the actual target workbook when exchanging files.