In Excel: use =NORM.DIST(x, mean, sd, TRUE) for the probability of being at or below x, and =NORM.INV(probability, mean, sd) to go the other way.
On this page8
Syntax
Arguments
| Argument | required / optional | Description |
|---|---|---|
x | required | The value to evaluate. |
mean | required | The distribution mean. |
standard_dev | required | The standard deviation. Must be positive. |
cumulative | required | TRUE for the cumulative probability, FALSE for the density. |
Related functions
Mean = 70.714 · Std deviation = 5.992
Need it as an auditable file?
Ships inside the linked template — formula-driven, unlocked, audit-ready.
What this does
NORM.DIST returns the probability that a normally distributed value falls at or below a point; NORM.INV takes a probability and returns the corresponding value. The cumulative argument is the one that catches people — TRUE gives the running probability you almost always want, FALSE gives the density curve height, which is only useful for plotting the bell shape. Their standardised siblings NORM.S.DIST and NORM.S.INV assume a mean of 0 and a standard deviation of 1, so they take z-scores directly. The assumption of normality is doing real work here and deserves a check before the numbers are trusted. Keep the inputs visible and clearly labelled and the whole thing stays auditable — anyone who opens the file later, including you, can see at a glance exactly what feeds the result and change one assumption without hunting through the formula. For “normdist function in excel”, the reliable version is a short checking loop, not just the first command that appears to work. Run it on a deliberately small range first, watch how the affected formula change, and only then apply the same setup to the full sheet. When a formula is involved, keep the inputs labelled beside it, reference cells instead of typing values, and apply number formatting only after the result checks out. That is what makes a calculation you can defend to a CFO or an auditor useful in real work: repeatable, auditable, and not dependent on memory or luck.
A worked example
The share of deliveries arriving within 5 days when the mean is 4.2 and the deviation 1.8: =NORM.DIST(5, 4.2, 1.8, TRUE) returns about 0.67. The service level that 95 % of orders meet: =NORM.INV(0.95, 4.2, 1.8) returns roughly 7.2 days. Plotting the bell curve itself needs the density form with FALSE. These two turn a mean and a deviation into service levels and thresholds, which is what capacity and SLA planning actually asks for. One habit worth forming early: name the cells that hold your inputs, so the formula reads in plain language instead of a string of cell addresses. A reviewer — or you in three months — can then follow the logic without decoding what B7 and D2 were supposed to mean, which is most of what makes a sheet maintainable.
In Google Sheets
If you are in Google Sheets rather than Excel, the good news is that the formula shown here is identical and the workflow barely changes — menus sit across the top instead of in a ribbon, and a few function names differ slightly, but anything you build here moves across with little or no rework. Nothing on this page is behind a login: the tool runs entirely in your browser, the formula is shown in full with one-click copy, and the steps work the same on Windows and Mac. That is the whole promise here — the exact answer, a way to prove it on your own numbers, and just enough context to make it stick. Here is the takeaway for “normdist function in excel”: copy the answer if you are busy, but if you have a spare few minutes, rebuild the example in Excel yourself with the tool above open beside it. That single pass — type it, run it, watch the result move when you change an input — is what turns a formula you found into a technique you trust. Keep your inputs labelled and referenced, never hard-coded, and the same sheet stays correct and auditable as it grows. Done that way, you will not need to look this up again, and you will be the person others ask.
Common mistakes
- Passing FALSE for cumulative and reading the result as a probability; that is the density, not a probability.
- Applying it to visibly skewed data, where the normal assumption misstates the tails badly.
- A standard deviation of zero or negative, which returns
#NUM!.
Frequently asked questions
What does the cumulative argument do?
TRUE returns the probability of being at or below x. FALSE returns the height of the density curve, used only for plotting.
How do I find the value at a given percentile?
=NORM.INV(probability, mean, sd). It is the inverse of NORM.DIST.
What is NORM.S.DIST?
The standardised version, assuming mean 0 and deviation 1, so it takes a z-score directly.